WO2019104583A1 - 最高温度点跟踪方法、装置和无人机 - Google Patents

最高温度点跟踪方法、装置和无人机 Download PDF

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Publication number
WO2019104583A1
WO2019104583A1 PCT/CN2017/113800 CN2017113800W WO2019104583A1 WO 2019104583 A1 WO2019104583 A1 WO 2019104583A1 CN 2017113800 W CN2017113800 W CN 2017113800W WO 2019104583 A1 WO2019104583 A1 WO 2019104583A1
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WIPO (PCT)
Prior art keywords
highest temperature
temperature point
coordinate
image
infrared camera
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PCT/CN2017/113800
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English (en)
French (fr)
Inventor
翁超
王铭熙
张伟
Original Assignee
深圳市大疆创新科技有限公司
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Publication date
Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to PCT/CN2017/113800 priority Critical patent/WO2019104583A1/zh
Priority to EP17933852.0A priority patent/EP3671681A4/en
Priority to CN201780029128.2A priority patent/CN109154815B/zh
Publication of WO2019104583A1 publication Critical patent/WO2019104583A1/zh
Priority to US16/728,383 priority patent/US11153494B2/en
Priority to US17/503,670 priority patent/US11798172B2/en

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/0094—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/48—Thermography; Techniques using wholly visual means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/12—Target-seeking control
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/143—Sensing or illuminating at different wavelengths
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/176—Urban or other man-made structures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/20—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from infrared radiation only
    • H04N23/23—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from infrared radiation only from thermal infrared radiation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/695—Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J2005/0077—Imaging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10048—Infrared image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/07—Target detection

Definitions

  • the embodiment of the invention relates to the technical field of drones, and in particular to a method, a device and a drone for tracking a maximum temperature point.
  • a gimbal is installed on the drone, and a camera can be mounted on the gimbal, and the camera can be used to take a picture. Therefore, during the flight of the drone, the drone can output the picture captured by the camera to the control terminal, and the control terminal displays the picture captured by the camera on the graphical user interface.
  • the camera mounted on the gimbal can be an infrared camera, and the infrared camera can sense the thermodynamic temperature of each object in the captured image. Since the thermodynamic temperature of each object in the image captured by the infrared camera may be different, therefore, the control is performed. The depth of the color of each object in the infrared image displayed on the terminal will also be different.
  • the highest temperature point of the screen needs to be displayed in real time at the center of the screen. Since the drone has a dynamic object during the flight or the captured image, the position of the highest temperature point changes. It may cause the highest temperature point not to be in the center of the picture.
  • the embodiment of the invention provides a method, a device and a drone for tracking the highest temperature point, which are used for tracking the highest temperature point, so that the highest temperature point is located at the target position of the image.
  • an embodiment of the present invention provides a method for tracking a highest temperature point, including:
  • an embodiment of the present invention provides a maximum temperature point tracking device, including: a memory and a processor;
  • the memory is configured to store program instructions
  • the processor is configured to invoke the program instructions stored in the memory to implement:
  • the pan-tilt rotation is controlled to adjust that a highest temperature point in the image acquired by the infrared camera is located at the target position.
  • an embodiment of the present invention provides a drone, including: a body, a pan/tilt, an infrared camera, and a highest temperature point tracking device according to the first aspect of the present invention; the cloud platform and the body Connecting; the pan/tilt is used to carry the infrared camera;
  • the highest temperature point tracking device is communicatively coupled to the pan/tilt and the infrared camera, respectively.
  • an embodiment of the present invention provides a chip, including: a memory and a processor;
  • the memory is configured to store program instructions
  • the processor is configured to invoke the program instructions stored in the memory to implement a highest temperature point tracking method according to the first aspect of the present invention.
  • the present invention provides a storage medium comprising: a readable storage medium and a computer program, the computer program for implementing the highest temperature point tracking method according to the first aspect of the present invention.
  • the highest temperature point tracking method, device and drone provided by the embodiment of the present invention obtain the first coordinate of the highest temperature point in the image sensed by the infrared camera, according to the first coordinate of the highest temperature point and the image
  • the coordinates of the target position determine the rotation angle of the pan/tilt head on which the infrared camera is mounted, and according to the rotation angle, the pan-tilt rotation is controlled to adjust that the highest temperature point in the image acquired by the infrared camera is located at the target position. Therefore, the infrared camera automatically tracks the highest temperature point. No matter how the highest temperature point changes, the highest temperature point will be at the target position in the image captured by the infrared camera, which is convenient for the user to observe the highest temperature point.
  • FIG. 1 is a schematic architectural diagram of an unmanned flight system 100 in accordance with an embodiment of the present invention
  • FIG. 2 is a flowchart of a method for tracking a highest temperature point according to an embodiment of the present invention
  • FIG. 3 is a flowchart of a method for tracking a highest temperature point according to another embodiment of the present invention.
  • FIG. 4 is a flowchart of a method for tracking a highest temperature point according to another embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of a maximum temperature point tracking device according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a maximum temperature point tracking device according to another embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of a drone according to an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of a drone according to another embodiment of the present invention.
  • Embodiments of the present invention provide a maximum temperature point tracking method, apparatus, and drone.
  • the drone may be a rotorcraft, for example, a multi-rotor aircraft propelled by air by a plurality of pushing devices, and embodiments of the present invention are not limited thereto.
  • FIG. 1 is a schematic architectural diagram of an unmanned flight system 100 in accordance with an embodiment of the present invention. This embodiment is described by taking a rotorcraft unmanned aerial vehicle as an example.
  • the unmanned aerial vehicle system 100 can include an unmanned aerial vehicle 110, a pan/tilt head 120, a display device 130, and a control device 140.
  • the unmanned aerial vehicle 110 may include a power system 150, a flight control system 160, and a rack.
  • the UAV 110 can be in wireless communication with the control device 140 and the display device 130.
  • the rack can include a fuselage and a tripod (also known as a landing gear).
  • the fuselage can include a center frame and One or more arms connected to the center frame, one or more arms extending radially from the center frame.
  • the stand is coupled to the fuselage for supporting when the UAV 110 is landing.
  • Power system 150 may include one or more electronic governors (referred to as ESCs) 151, one or more propellers 153, and one or more electric machines 152 corresponding to one or more propellers 153, wherein motor 152 is coupled Between the electronic governor 151 and the propeller 153, the motor 152 and the propeller 153 are disposed on the arm of the unmanned aerial vehicle 110; the electronic governor 151 is configured to receive the driving signal generated by the flight control system 160 and provide driving according to the driving signal. Current is supplied to the motor 152 to control the rotational speed of the motor 152. Motor 152 is used to drive propeller rotation to power the flight of unmanned aerial vehicle 110, which enables unmanned aerial vehicle 110 to achieve one or more degrees of freedom of motion.
  • ESCs electronic governors
  • the UAV 110 can be rotated about one or more axes of rotation.
  • the above-described rotating shaft may include a roll axis, a yaw axis, and a pitch axis.
  • the motor 152 can be a DC motor or an AC motor.
  • the motor 152 may be a brushless motor or a brushed motor.
  • Flight control system 160 may include flight controller 161 and sensing system 162.
  • the sensing system 162 is used to measure the attitude information of the unmanned aerial vehicle, that is, the position information and state information of the UAV 110 in space, for example, three-dimensional position, three-dimensional angle, three-dimensional speed, three-dimensional acceleration, and three-dimensional angular velocity.
  • Sensing system 162 can include, for example, at least one of a gyroscope, an ultrasonic sensor, an electronic compass, an Inertial Measurement Unit (IMU), a vision sensor, a global navigation satellite system, and a barometer.
  • the global navigation satellite system can be a Global Positioning System (GPS).
  • GPS Global Positioning System
  • the flight controller 161 is used to control the flight of the unmanned aerial vehicle 110, for example, the flight of the unmanned aerial vehicle 110 can be controlled based on the attitude information measured by the sensing system 162. It should be understood that the flight controller 161 may control the UAV 110 in accordance with pre-programmed program instructions, or may control the UAV 110 in response to one or more control commands from the control device 140.
  • the pan/tilt 120 can include a motor 122.
  • the pan/tilt is used to carry the imaging device 123.
  • the flight controller 161 can control the motion of the platform 120 via the motor 122.
  • the platform 120 may further include a controller for controlling the motion of the platform 120 by controlling the motor 122.
  • the platform 120 can be independent of the UAV 110 or a portion of the UAV 110.
  • the motor 122 can be a DC motor or an AC motor.
  • the motor 122 may be a brushless motor or a brushed motor.
  • the gimbal can be located at no one.
  • the top of the aircraft can also be located at the bottom of the UAV.
  • the imaging device 123 may be, for example, a device for capturing an image such as a camera or a video camera, and the imaging device 123 may communicate with the flight controller and perform shooting under the control of the flight controller.
  • the imaging device 123 of the present embodiment includes at least a photosensitive element, such as a Complementary Metal Oxide Semiconductor (CMOS) sensor or a Charge-coupled Device (CCD) sensor.
  • CMOS Complementary Metal Oxide Semiconductor
  • CCD Charge-coupled Device
  • Display device 130 is located at the ground end of unmanned aerial vehicle system 100, can communicate with unmanned aerial vehicle 110 wirelessly, and can be used to display attitude information for unmanned aerial vehicle 110. In addition, an image taken by the imaging device can also be displayed on the display device 130. It should be understood that the display device 130 may be a stand-alone device or may be integrated in the control device 140.
  • the control device 140 is located at the ground end of the unmanned aerial vehicle system 100 and can communicate with the unmanned aerial vehicle 110 in a wireless manner for remote manipulation of the unmanned aerial vehicle 110.
  • FIG. 2 is a flowchart of a method for tracking a maximum temperature point according to an embodiment of the present invention. As shown in FIG. 2, the method in this embodiment may include:
  • an image can be acquired by an infrared camera, and the infrared camera can sense the temperature in the image when the image is acquired.
  • the temperature is high, and in some places, the temperature is low, and the highest temperature exists in the temperature, and the temperature is the highest temperature.
  • the position is called the highest temperature point, and the coordinates of the highest temperature point are obtained.
  • the coordinates of the highest temperature point in the acquired image are referred to as the first coordinates.
  • the rotation angle of the pan/tilt is determined according to the first coordinate of the highest temperature point in the image and the coordinates of the target position in the image, and the infrared camera is mounted on the pan/tilt, and then the cloud is controlled according to the rotation angle.
  • the rotation of the table for example: controlling the pan/tilt to rotate the above rotation angle, since the infrared camera is mounted on the pan/tilt, the rotation of the gimbal drives the rotation of the infrared camera, so that the infrared phase can be The machine adjusts to the highest temperature point in the image captured by the infrared camera at the target position.
  • the infrared camera automatically tracks the highest temperature point. No matter how the highest temperature point changes, the highest temperature point will be at the target position in the image captured by the infrared camera, which is convenient for the user to observe the highest temperature point.
  • the image acquired by the infrared camera is also displayed on the display interface, wherein the highest temperature point in the image is located at the target position of the image.
  • the user can accurately determine the highest temperature point by the target position of the image displayed on the display interface.
  • the target location is the exact center of the image. In this way, when the user observes the highest temperature point, it is only necessary to observe the center position of the image to quickly and clearly know the highest temperature point.
  • FIG. 3 is a flowchart of a method for tracking a maximum temperature point according to another embodiment of the present invention. As shown in FIG. 3, the method in this embodiment may include:
  • an implementation manner of S202 includes the following S302-S303.
  • the desired coordinate of the highest temperature point that is, the coordinate of the desired highest temperature point
  • the desired coordinate of the highest temperature point may be determined. Then, based on the desired coordinates of the highest temperature point and the coordinates of the target position in the image, the rotation angle of the gimbal is determined.
  • the infrared camera by obtaining the first coordinate of the highest temperature point and the temperature in the image sensed by the infrared camera, and then determining the desired coordinate of the highest temperature point according to the temperature of the highest temperature point and the first coordinate, and according to Determining, by the desired coordinates, coordinates of the target position in the image, determining a rotation angle of the pan/tilt head on which the infrared camera is mounted, and controlling the pan-tilt rotation according to the rotation angle to adjust an image acquired by the infrared camera
  • the highest temperature point is at the target location.
  • the embodiment can predetermine the desired coordinates of the highest temperature point, and then adjust the pan/tilt so that the infrared camera captures the highest temperature point to the target position in the image, the infrared camera automatically tracks the highest temperature point, regardless of the highest temperature point. Change, the highest temperature point will be in the target position in the image captured by the infrared camera, so that the user can observe the highest temperature point.
  • a possible implementation manner of the foregoing S302 is: taking the image as the current frame image as an example, and determining the temperature of the highest temperature point in the current frame image sensed by the infrared camera. Whether the temperature of the sensed highest temperature point is in the highest temperature confidence interval, if the temperature of the highest temperature point sensed by the infrared camera is within the highest temperature confidence zone, the desired coordinates can be determined by two implementations.
  • One solution is to determine that the first coordinate of the highest temperature point in the current frame image is the desired coordinate of the highest temperature point. That is, the desired coordinate of the highest temperature point is equal to the first coordinate.
  • Another solution is: determining the desired coordinate according to a first coordinate of a highest temperature point in the current frame image and a first coordinate of a highest temperature point in an N frame image before the current frame sensed by the infrared camera .
  • the N-frame image is a continuous N-frame image in which the temperature of the highest temperature point is within the highest temperature confidence interval, and the N is an integer greater than or equal to 1.
  • the current frame image is the T-th frame image
  • the TN frame image, the T-(N-1) frame image, the ..., the T-1 frame image, and the T-th frame image sensed by the infrared camera are used.
  • the coordinates of the highest temperature point in the middle determine the desired coordinates of the highest temperature point, and the highest temperature in the TN frame image, the T-(N-1) frame image, ..., the T-1 frame image, and the T-frame image
  • the temperature of the point is within the highest temperature confidence interval.
  • the temperature of the highest temperature point in the image of the T-(N-1) frame is not within the highest temperature confidence interval, and the temperature of the highest temperature point in the image of the T-(N+1) frame is at the highest temperature.
  • the N frames before the current frame are: T-(N+1) frame image, TN frame image, T-(N-2) Frame image, ..., T-1 frame image, T frame image.
  • the temperature of the highest temperature point in the K-frame image before the current frame described below is located within the highest temperature range. See also the description here.
  • determining whether the temperature of the highest temperature point in the frame image is in the highest temperature confidence interval is mainly by determining the variance between the temperature of the highest temperature point in the frame image and the temperature of the highest temperature point in the K frame image before the frame image or Whether the standard deviation is less than the preset value is achieved.
  • the K-frame image before the current frame is the T-K frame image
  • the T-(K-1) frame image ..., the T-1 frame image.
  • the temperature of the highest temperature point in the current frame image is located in the highest temperature confidence interval, and other frame images are similar, and are not described herein again.
  • the current frame image is considered The temperature at the highest temperature point in the medium is not within the highest temperature confidence interval. or,
  • the implementation manner of determining the desired coordinate may be The following are included, but the embodiment is not limited thereto.
  • performing a least squares operation on the first coordinate of the highest temperature point in the N frame image before the current frame and the first coordinate of the highest temperature point in the current frame image The desired coordinates.
  • the coordinates of the highest temperature point in the TN frame image sensed by the infrared camera, the coordinates of the highest temperature point in the T-(N-1) frame image sensed by the infrared camera, ..., the infrared camera sense The coordinates of the highest temperature point in the measured T-1 frame image and the coordinates of the highest temperature point in the T-frame image sensed by the infrared camera (ie, the N+1 coordinates) are subjected to a least squares operation, and the operation result is obtained. Determined as the desired coordinates.
  • the expected coordinates are determined according to a first coordinate of a highest temperature point in an N frame image before the current frame and an average value of the first coordinates of the highest temperature point in the current frame image.
  • the coordinates of the highest temperature point in the TN frame image sensed by the infrared camera, the coordinates of the highest temperature point in the T-(N-1) frame image sensed by the infrared camera, ..., the infrared camera sense The average of the coordinates of the highest temperature point in the measured T-1 frame image and the coordinates of the highest temperature point in the T-frame image sensed by the infrared camera (ie, the N+1 coordinates) are determined as the desired coordinates.
  • the expected coordinates are determined according to a first coordinate of a highest temperature point in an N frame image before the current frame and a weighted average of the first coordinates of the highest temperature point in the current frame image.
  • the coordinates of the highest temperature point in the TN frame image sensed by the infrared camera, the coordinates of the highest temperature point in the T-(N-1) frame image sensed by the infrared camera, ..., the infrared camera sense The weighted average of the coordinates of the highest temperature point in the measured T-1 frame image and the coordinates of the highest temperature point in the T-frame image sensed by the infrared camera (ie, the N+1 coordinates) is determined as the desired coordinates.
  • the last determined desired coordinate is the current desired coordinate, that is, determining that the last determined desired coordinate is S302.
  • the desired coordinates to be determined if the temperature of the highest temperature point in the current frame image is not located in the highest temperature confidence interval, it is determined that the last determined desired coordinate is the current desired coordinate, that is, determining that the last determined desired coordinate is S302. The desired coordinates to be determined.
  • FIG. 4 is a flowchart of a method for tracking a maximum temperature point according to another embodiment of the present invention. As shown in FIG. 4, the method in this embodiment may include:
  • S402. Determine, according to the visual tracking, a second coordinate of an expected highest temperature point in the image acquired by the infrared camera.
  • the execution order of S401 and S402 is in no particular order.
  • the visual tracking it is possible to determine the highest expected image in the image captured by the infrared camera.
  • the temperature point so that the coordinates of the expected highest temperature point can be determined, wherein the coordinates of the expected highest temperature point determined by visual tracking are referred to as second coordinates.
  • the code stream feature of the expected highest temperature point is also acquired prior to performing S402.
  • one possible implementation manner of S402 may include: S4021 and S4022.
  • S4021 Acquire an infrared code stream of an image collected by the infrared camera.
  • S4022 Perform visual tracking on the infrared code stream according to the code stream feature to determine the second coordinate.
  • the code stream feature of the expected highest temperature point acquired may be an infrared stream feature.
  • an infrared code stream of an image is obtained, and the image is an image acquired by an infrared camera, and then the infrared code stream of the image is visually tracked according to the code stream feature of the expected highest temperature point, thereby determining an expected image in the image.
  • the second coordinate of the highest temperature point is obtained, and the image is an image acquired by an infrared camera, and then the infrared code stream of the image is visually tracked according to the code stream feature of the expected highest temperature point, thereby determining an expected image in the image.
  • the second coordinate of the highest temperature point is a code stream feature of the expected highest temperature point.
  • the code stream feature may be acquired in real time or may be pre-stored in the memory.
  • the real-time acquisition of the code stream feature is: determining the code stream feature of the expected highest temperature point according to the code stream feature of the highest temperature point corresponding to the expected M coordinate determined by the previous M times, where M is an integer greater than or equal to 1. .
  • the code stream feature of the highest temperature point corresponding to the desired coordinate in the image may also be obtained after determining the desired coordinate, and then determining the current expected maximum according to the code stream feature of the highest temperature point corresponding to the expected coordinate determined by the previous M times.
  • the code stream characteristics of the temperature point may be obtained after determining the desired coordinate, and then determining the current expected maximum according to the code stream feature of the highest temperature point corresponding to the expected coordinate determined by the previous M times.
  • the desired coordinates of the highest temperature point are determined according to the temperature of the highest temperature point sensed by the infrared camera, and the first coordinate of the highest temperature point and the second coordinate of the expected highest temperature point obtained by visual tracking.
  • a possible implementation manner of the foregoing S403 is: taking the image as the current frame image as an example, after obtaining the temperature of the highest temperature point in the current frame image sensed by the infrared camera, determining the infrared camera Whether the temperature of the sensed highest temperature point is in the highest temperature confidence interval, if the temperature of the highest temperature point sensed by the infrared camera is within the highest temperature confidence zone, the desired coordinates can be determined by two implementations.
  • One solution is: the highest temperature point in the current frame image sensed by the infrared camera The first coordinate and the second coordinate of the expected highest temperature point in the current frame image determine the desired coordinate.
  • the implementation manner of the solution may include the following, but the embodiment is not limited thereto.
  • performing a least squares operation on the first coordinate of the highest temperature point in the current frame image and the second coordinate of the expected highest temperature point in the current frame image to obtain the desired coordinate For example, the coordinates of the highest temperature point in the current frame image sensed by the infrared camera and the coordinates of the expected temperature point in the current frame image obtained by visual tracking (ie, the two coordinates) are subjected to least squares operation, and the operation result is determined. For the desired coordinates.
  • the desired coordinate is determined according to an average value of a first coordinate of a highest temperature point in the current frame image and a second coordinate of a second coordinate of the expected highest temperature point in the current frame image. For example, the coordinates of the highest temperature point in the current frame image sensed by the infrared camera and the average of the coordinates of the expected temperature point (ie, the two coordinates) in the current frame image obtained by visual tracking are determined as desired coordinates.
  • the weighted average of the first coordinate of the highest temperature point in the current frame image and the second coordinate of the expected highest temperature point in the current frame image determines the desired coordinate. For example, the coordinates of the highest temperature point in the current frame image sensed by the infrared camera and the weighted average of the coordinates of the expected temperature point (ie, the two coordinates) in the current frame image obtained by visual tracking are determined as desired coordinates.
  • the other solution is: according to the first coordinate of the highest temperature point in the current frame image and the second coordinate of the expected highest temperature point in the current frame image, and the highest temperature point in the N frame image before the current frame.
  • the first coordinate and the second coordinate of the expected highest temperature point in the N frame image preceding the current frame determine the desired coordinate.
  • the N frame image before the current frame is a continuous N frame image in which the temperature of the highest temperature point is within the highest temperature confidence interval, and the N is an integer greater than or equal to 1.
  • the implementation manner of the solution may include the following, but the embodiment is not limited thereto.
  • the first coordinate of the highest temperature point in the N frame image before the current frame and the second coordinate of the expected highest temperature point in the N frame image before the current frame, and the highest temperature point in the current frame image are subjected to a least squares operation to obtain the desired coordinates.
  • the coordinates of the highest temperature point in the image of the T-N frame sensed by the infrared camera and the expected temperature in the image of the T-N frame obtained by visual tracking The coordinates of the degree point, the coordinates of the highest temperature point in the image of the T-(N-1) frame sensed by the infrared camera, and the coordinates of the expected temperature point in the image of the T-(N-1) frame obtained by visual tracking, ..., the coordinates of the highest temperature point in the image of the T-1 frame sensed by the infrared camera, and the coordinates of the expected temperature point in the image of the T-1 frame obtained by visual tracking, and the Tth frame sensed by the infrared camera
  • the coordinates of the highest temperature point in the image and the coordinates of the expected temperature point in the T-frame image obtained by visual tracking are subjected to a least squares operation, and the operation result is determined as the desired coordinates.
  • the highest temperature in the current frame image is determined by the first coordinate of the point and the average of the second coordinates of the expected highest temperature point in the current frame image. For example, the coordinates of the highest temperature point in the TN frame image sensed by the infrared camera and the coordinates of the expected temperature point in the TN frame image obtained by visual tracking, and the T-(N-1) sensed by the infrared camera.
  • the coordinates of the highest temperature point in the frame image and the coordinates of the expected temperature point in the T-(N-1) frame image obtained by visual tracking, ..., the highest temperature in the image of the T-1 frame sensed by the infrared camera The coordinates of the point and the coordinates of the expected temperature point in the image of the T-1 frame obtained by visual tracking, the coordinates of the highest temperature point in the image of the T-th frame sensed by the infrared camera, and the expected image in the T-frame image obtained by visual tracking
  • the average of the coordinates of the temperature point i.e., the 2*(N+1) coordinates
  • the highest temperature in the current frame image is determined by a weighted average of the first coordinate of the point and the second coordinate of the expected highest temperature point in the current frame image. For example, the coordinates of the highest temperature point in the TN frame image sensed by the infrared camera and the coordinates of the expected temperature point in the TN frame image obtained by visual tracking, and the T-(N-1) sensed by the infrared camera.
  • the coordinates of the highest temperature point in the frame image and the coordinates of the expected temperature point in the T-(N-1) frame image obtained by visual tracking, ..., the highest temperature in the image of the T-1 frame sensed by the infrared camera The coordinates of the point and the coordinates of the expected temperature point in the image of the T-1 frame obtained by visual tracking, the coordinates of the highest temperature point in the image of the T-th frame sensed by the infrared camera, and the expected image in the T-frame image obtained by visual tracking
  • the weighted average of the coordinates of the temperature points i.e., these 2*(N+1) coordinates is determined as the desired coordinates.
  • determining whether the temperature of the highest temperature point in the frame image is located in the highest temperature confidence interval may be by determining the temperature of the highest temperature point in the frame image and the highest in the K frame image before the current frame. Whether the variance or standard deviation between the temperatures of the temperature points is less than a preset value is achieved.
  • the last determined desired coordinate is the current desired coordinate, that is, determining that the last determined desired coordinate is in S302. The desired coordinates to be determined.
  • the temperature and coordinates of the highest temperature point in the frame image sensed by the infrared camera, and the coordinates of the highest temperature point in the frame image are obtained by visual tracking, and the expected coordinates of the highest temperature point are determined to be closer according to the above parameters.
  • the actual maximum temperature point is to ensure that the highest temperature point in the next frame image is displayed in real time at the target position of the image.
  • the embodiment of the present invention further provides a computer storage medium, where the computer storage medium stores program instructions, and the program execution may include the highest temperature point tracking method in FIG. 2 to FIG. 4 and its corresponding embodiments. Some or all of the steps.
  • FIG. 5 is a schematic diagram of a structure of a maximum temperature point tracking device according to an embodiment of the present invention.
  • the highest temperature point tracking device 500 of the present embodiment may include a memory 501 and a processor 502.
  • the processor 502 may be a central processing unit (CPU), and the processor 502 may be another general-purpose processor, a digital signal processor (DSP), or an application specific integrated circuit (ASIC). ), a Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, and the like.
  • the general purpose processor may be a microprocessor or the processor or any conventional processor or the like.
  • a memory 501 configured to store program instructions
  • the processor 502 is configured to invoke the program instructions stored in the memory 501 to implement:
  • the pan-tilt rotation is controlled to adjust that a highest temperature point in the image acquired by the infrared camera is located at the target position.
  • the processor 502 is further configured to: acquire a temperature of a highest temperature point in an image sensed by the infrared camera;
  • the processor 502 determines, according to the first coordinate of the highest temperature point and the coordinates of the target position in the image, when the rotation angle of the pan/tilt of the infrared camera is mounted, specifically for: according to the highest temperature point a temperature and the first coordinate, determining a desired coordinate of the highest temperature point; and determining a rotation angle of the pan/tilt based on the desired coordinate and a coordinate of the target position in the image.
  • the processor 502 is specifically configured to:
  • the N-frame image is a continuous N-frame image in which the temperature of the highest temperature point is within the highest temperature confidence interval, and the N is an integer greater than or equal to 1.
  • the processor 502 is further configured to determine an expected highest image in the image acquired by the infrared camera according to the visual tracking before determining the desired coordinate of the highest temperature point according to the temperature and the first coordinate of the highest temperature point.
  • the processor 502 is configured to determine, according to the temperature of the highest temperature point and the first coordinate, a desired coordinate of the highest temperature point, according to the temperature of the highest temperature point, the first coordinate, and the The second coordinate of the expected maximum temperature point is determined, and the desired coordinate of the highest temperature point is determined.
  • the processor 502 is further configured to acquire a code stream feature of an expected highest temperature point before determining a second coordinate of an expected highest temperature point in the image acquired by the infrared camera according to the visual tracking;
  • the processor 502 determines the highest temperature in the image acquired by the infrared camera according to the visual tracking
  • the second coordinate of the point is specifically used to: acquire an infrared code stream of the image collected by the infrared camera; and perform visual tracking on the infrared code stream according to the code stream feature to determine the second coordinate.
  • the processor 502 is configured to determine a code stream feature of an expected highest temperature point according to a code stream feature of a highest temperature point corresponding to the M coordinate determined by the previous M times; where the M is greater than or An integer equal to 1.
  • the processor 502 is specifically configured to:
  • the N-frame image is a continuous N-frame image in which the temperature of the highest temperature point is within the highest temperature confidence interval, and the N is an integer greater than or equal to 1.
  • the processor 502 is further configured to determine that the last determined desired coordinate is the current desired coordinate when the temperature of the highest temperature point in the current frame image is not located in the highest temperature confidence interval.
  • the temperature of the highest temperature point in the current frame image sensed by the infrared camera is located in the highest temperature confidence interval, and includes:
  • the temperature of the highest temperature point in the current frame image when the variance or standard deviation between the temperature of the highest temperature point in the current frame image and the temperature of the highest temperature point in the K frame image before the current frame is less than a preset value Located in the highest temperature confidence interval;
  • the K-frame image is a continuous K-frame image in which the temperature of the highest temperature point is within the highest temperature confidence interval, and the K is an integer greater than or equal to 1.
  • the processor 502 is specifically configured to:
  • the at least two coordinates comprise at least two first coordinates, or the at least two The coordinates include at least one first coordinate and at least one second coordinate.
  • the target location is the exact center of the image.
  • the device in this embodiment may be used to implement the technical solutions of the foregoing method embodiments of the present invention, and the implementation principles and technical effects thereof are similar, and details are not described herein again.
  • FIG. 6 is a schematic structural diagram of a maximum temperature point tracking device according to another embodiment of the present invention. As shown in FIG. 6, the highest temperature point tracking device 500 of the present embodiment may further include the embodiment shown in FIG. : Display interface 503.
  • the display interface 503 is configured to display the infrared camera after the processor 502 controls the pan-tilt rotation according to the rotation angle to adjust the highest temperature point in the image captured by the infrared camera to be located at the target position. An image in which the highest temperature point in the image is at the target location of the image.
  • the device in this embodiment may be used to implement the technical solutions of the foregoing method embodiments of the present invention, and the implementation principles and technical effects thereof are similar, and details are not described herein again.
  • FIG. 7 is a schematic structural diagram of a drone according to an embodiment of the present invention.
  • the drone 1000 of the present embodiment includes: a highest temperature point tracking device 500, a body 600, a pan/tilt 700, and an infrared camera 800.
  • the pan/tilt 700 is connected to the body 600; the pan/tilt 700 is used to mount the infrared camera 800.
  • the highest temperature point tracking device 500 is communicatively coupled to the pan/tilt 700 and the infrared camera 800, respectively.
  • the highest temperature point tracking device 500 can adopt the structure of the embodiment shown in FIG. 5 or FIG. 6 , which can correspondingly implement the technical solutions of the foregoing method embodiments of the present invention, and the implementation principle and technical effects are similar. I won't go into details here.
  • FIG. 8 is a schematic structural diagram of a drone according to another embodiment of the present invention.
  • the drone 1000 of the present embodiment may further include: a display device 900 based on the embodiment shown in FIG. 7;
  • the display device 900 is communicatively coupled to the infrared camera 800;
  • the display device 900 is configured to display an image acquired by the infrared camera 800, wherein a highest temperature point in the image is located at the target position of the image.
  • the highest temperature point tracking device 500 may be part of the flight control system of the drone 1000, or the highest temperature point tracking device 500 may be part of the control device at the ground end of the drone 1000.
  • the foregoing program may be stored in a computer readable storage medium, and when executed, the program includes the steps of the foregoing method embodiment; and the foregoing storage medium includes: read only memory (Read-Only Memory, ROM), Random Access Memory (RAM), disk or optical disk, and other media that can store program code.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • disk or optical disk and other media that can store program code.

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Abstract

一种最高温度点跟踪方法、装置和无人机，此方法包括：获取红外相机感测的图像中最高温度点的第一坐标，根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度，根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。因此使得红外相机自动跟踪最高温度点拍摄，无论最高温度点如何变化，最高温度点将处于红外相机采集的图像中的目标位置，便于使用者观察最高温度点。

Description

最高温度点跟踪方法、装置和无人机 技术领域
本发明实施例涉及无人机技术领域，尤其涉及一种最高温度点跟踪方法、装置和无人机。
背景技术
无人机上设置有云台，而且云台上可以搭载有相机，相机可以用于拍摄画面。因此，无人机在飞行过程中，无人机可以将相机拍摄到的画面输出给控制终端，控制终端在图形用户界面上显示相机拍摄到的画面。其中，云台上搭载的相机可以为红外相机，红外相机可以感测其拍摄到的画面中各物体的热力学温度，由于红外相机拍摄到的画面中各物体的热力学温度可能不同，因此，在控制终端上显示的红外图像中的各物体的颜色的深度也会不同，其中，若物体的温度越高，画面中该物体的颜色越深，因此，通过无人机上搭载的红外相机拍摄到的画面可以用于帮助消防员定位房屋中的火源、检测农作物健康、以及与警犬一起进行搜救行动等。但是在一些应用场景中，需要在画面的中心位置实时显示画面的最高温度点，由于无人机在飞行过程中或者拍摄到的画面存在动态的物体，这会使得最高温度点的位置发生变化，可能会造成最高温度点并未处于拍摄画面的中心位置上。
发明内容
本发明实施例提供一种最高温度点跟踪方法、装置和无人机，用于实现跟踪最高温度点拍摄，使得最高温度点位于图像的目标位置。
第一方面，本发明实施例提供一种最高温度点跟踪方法，包括：
获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红外相机采集的图像；
根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度；
根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像 中最高温度点位于所述目标位置。
第二方面，本发明实施例提供一种最高温度点跟踪装置，包括：存储器和处理器；
所述存储器，用于存储程序指令；
所述处理器，用于调用所述存储器中存储的所述程序指令以实现：
获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红外相机采集的图像；
根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度；
根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
第三方面，本发明实施例提供一种无人机，包括：机体、云台、红外相机以及如第一方面本发明实施例所述的最高温度点跟踪装置；所述云台与所述机体连接；所述云台用于搭载所述红外相机；
所述最高温度点跟踪装置分别与所述云台和所述红外相机通信连接。
第四方面，本发明实施例提供一种芯片，包括：存储器和处理器；
所述存储器，用于存储程序指令；
所述处理器，用于调用所述存储器中存储的所述程序指令以实现如第一方面本发明实施例所述的最高温度点跟踪方法。
第五方面，本发明提供一种存储介质，包括：可读存储介质和计算机程序，所述计算机程序用于实现如第一方面本发明实施例所述的最高温度点跟踪方法。
本发明实施例提供的最高温度点跟踪方法、装置和无人机，通过获取红外相机感测的图像中最高温度点的第一坐标，根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度，根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。因此使得红外相机自动跟踪最高温度点拍摄，无论最高温度点如何变化，最高温度点将处于红外相机采集的图像中的目标位置，便于使用者观察最高温度点。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作一简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是根据本发明的实施例的无人飞行***100的示意性架构图；
图2为本发明一实施例提供的最高温度点跟踪方法的流程图；
图3为本发明另一实施例提供的最高温度点跟踪方法的流程图；
图4为本发明另一实施例提供的最高温度点跟踪方法的流程图；
图5为本发明一实施例提供的最高温度点跟踪装置的结构示意图；
图6为本发明另一实施例提供的最高温度点跟踪装置的结构示意图；
图7为本发明一实施例提供的无人机的结构示意图；
图8为本发明另一实施例提供的无人机的结构示意图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
本发明的实施例提供了最高温度点跟踪方法、装置和无人机。无人机可以是旋翼飞行器(rotorcraft)，例如，由多个推动装置通过空气推动的多旋翼飞行器，本发明的实施例并不限于此。
图1是根据本发明的实施例的无人飞行***100的示意性架构图。本实施例以旋翼无人飞行器为例进行说明。
无人飞行***100可以包括无人飞行器110、云台120、显示设备130和控制装置140。其中，无人飞行器110可以包括动力***150、飞行控制***160和机架。无人飞行器110可以与控制装置140和显示设备130进行无线通信。
机架可以包括机身和脚架(也称为起落架)。机身可以包括中心架以及 与中心架连接的一个或多个机臂，一个或多个机臂呈辐射状从中心架延伸出。脚架与机身连接，用于在无人飞行器110着陆时起支撑作用。
动力***150可以包括一个或多个电子调速器(简称为电调)151、一个或多个螺旋桨153以及与一个或多个螺旋桨153相对应的一个或多个电机152，其中电机152连接在电子调速器151与螺旋桨153之间，电机152和螺旋桨153设置在无人飞行器110的机臂上；电子调速器151用于接收飞行控制***160产生的驱动信号，并根据驱动信号提供驱动电流给电机152，以控制电机152的转速。电机152用于驱动螺旋桨旋转，从而为无人飞行器110的飞行提供动力，该动力使得无人飞行器110能够实现一个或多个自由度的运动。在某些实施例中，无人飞行器110可以围绕一个或多个旋转轴旋转。例如，上述旋转轴可以包括横滚轴、偏航轴和俯仰轴。应理解，电机152可以是直流电机，也可以交流电机。另外，电机152可以是无刷电机，也可以是有刷电机。
飞行控制***160可以包括飞行控制器161和传感***162。传感***162用于测量无人飞行器的姿态信息，即无人飞行器110在空间的位置信息和状态信息，例如，三维位置、三维角度、三维速度、三维加速度和三维角速度等。传感***162例如可以包括陀螺仪、超声传感器、电子罗盘、惯性测量单元(Inertial Measurement Unit，IMU)、视觉传感器、全球导航卫星***和气压计等传感器中的至少一种。例如，全球导航卫星***可以是全球定位***(Global Positioning System，GPS)。飞行控制器161用于控制无人飞行器110的飞行，例如，可以根据传感***162测量的姿态信息控制无人飞行器110的飞行。应理解，飞行控制器161可以按照预先编好的程序指令对无人飞行器110进行控制，也可以通过响应来自控制装置140的一个或多个控制指令对无人飞行器110进行控制。
云台120可以包括电机122。云台用于携带成像装置123。飞行控制器161可以通过电机122控制云台120的运动。可选地，作为另一实施例，云台120还可以包括控制器，用于通过控制电机122来控制云台120的运动。应理解，云台120可以独立于无人飞行器110，也可以为无人飞行器110的一部分。应理解，电机122可以是直流电机，也可以是交流电机。另外，电机122可以是无刷电机，也可以是有刷电机。还应理解，云台可以位于无人 飞行器的顶部，也可以位于无人飞行器的底部。
成像装置123例如可以是照相机或摄像机等用于捕获图像的设备，成像装置123可以与飞行控制器通信，并在飞行控制器的控制下进行拍摄。本实施例的成像装置123至少包括感光元件，该感光元件例如为互补金属氧化物半导体(Complementary Metal Oxide Semiconductor，CMOS)传感器或电荷耦合元件(Charge-coupled Device，CCD)传感器。
显示设备130位于无人飞行***100的地面端，可以通过无线方式与无人飞行器110进行通信，并且可以用于显示无人飞行器110的姿态信息。另外，还可以在显示设备130上显示成像装置拍摄的图像。应理解，显示设备130可以是独立的设备，也可以集成在控制装置140中。
控制装置140位于无人飞行***100的地面端，可以通过无线方式与无人飞行器110进行通信，用于对无人飞行器110进行远程操纵。
应理解，上述对于无人飞行***各组成部分的命名仅是出于标识的目的，并不应理解为对本发明的实施例的限制。
图2为本发明一实施例提供的最高温度点跟踪方法的流程图，如图2所示，本实施例的方法可以包括：
S201、获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红外相机采集的图像。
本实施例可以通过红外相机采集图像，并且红外相机在采集图像时可以感测该图像中的温度，有些地方温度高，有些地方温度低，这些温度中存在最高温度，将温度为该最高温度的位置称为最高温度点，并获取该最高温度点的坐标，此处将获取的图像中最高温度点的坐标称为第一坐标。
S202、根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度。
S203、根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
本实施例中，根据上述图像中最高温度点的第一坐标，以及该图像中目标位置的坐标，确定云台的旋转角度，该云台上搭载有红外相机，然后根据该旋转角度，控制云台旋转，例如：控制该云台旋转上述旋转角度，由于红外相机搭载在云台上，云台的旋转带动红外相机的旋转，这样可以将红外相 机调整至该红外相机采集的图像中最高温度点位于该目标位置。
本实施例中，通过获取红外相机感测的图像中最高温度点的第一坐标，根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度，根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。因此使得红外相机自动跟踪最高温度点拍摄，无论最高温度点如何变化，最高温度点将处于红外相机采集的图像中的目标位置，便于使用者观察最高温度点。
在一些实施例中，在执行上述S203之后，还在显示界面显示所述红外相机采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。用户通过显示界面显示的图像的目标位置可以准确确定最高温度点。
在一些实施例中，上述目标位置为图像的正中心。这样使用者在观察最高温度点时，只需观察图像的正中心位置就即快速且一目了然地获知最高温度点。
图3为本发明另一实施例提供的最高温度点跟踪方法的流程图，如图3所示，本实施例的方法可以包括：
S301、获取红外相机感测的图像中最高温度点的第一坐标以及温度，所述图像为所述红外相机采集的图像。
本实施例中，不仅获取红外相机感测的图像中最高温度点的坐标(即第一坐标)，还获取该红外相机感测的该最高温度点的温度。相应地，S202的一种实现方式包括如下S302-S303。
S302、根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标。
S303、根据所述期望坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度。
本实施例中，根据该最高温度点的温度以及该最高温度点的第一坐标，可以确定最高温度点的期望坐标，即期望最高温度点的坐标。然后根据最高温度点的期望坐标以及图像中目标位置的坐标，确定云台的旋转角度。
其中，根据一个坐标和另一个坐标，从一个坐标位置处旋转至另一个坐标位置的具体过程可以参见现有技术中的相关描述，此处不再赘述。
S304、根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集 的图像中最高温度点位于所述目标位置。
本实施例中，S304的具体实现过程可以参见图2所示实施例中的相关描述，此处不再赘述。
本实施例中，通过获取红外相机感测的图像中最高温度点的第一坐标以及温度，然后根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标，以及根据所述期望坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度，再根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。由于本实施例可以预先确定最高温度点的期望坐标，然后调整云台，以便红外相机将最高温度点拍摄到图像中的目标位置，实现了红外相机自动跟踪最高温度点拍摄，无论最高温度点如何变化，最高温度点将处于红外相机采集的图像中的目标位置，便于使用者观察最高温度点。
在一些实施例中，上述S302的一种可能的实现方式为：以上述图像为当前帧图像为例，在获取到红外相机感测的当前帧图像中最高温度点的温度后，判断该红外相机感测的最高温度点的温度是否位于最高温度置信区间，如果该红外相机感测的最高温度点的温度位于该最高温度置信区内，则可以通过两种实现方案来确定期望坐标。
其中，一种方案为：确定该当前帧图像中该最高温度点的第一坐标为最高温度点的期望坐标。即最高温度点的期望坐标等于该第一坐标。
另一种方案为：根据所述当前帧图像中最高温度点的第一坐标，以及所述红外相机感测的当前帧之前的N帧图像中最高温度点的第一坐标，确定所述期望坐标。其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
例如：当前帧图像为第T帧图像，则根据红外相机感测出的第T-N帧图像、第T-(N-1)帧图像、...、第T-1帧图像、第T帧图像中最高温度点的坐标，确定最高温度点的期望坐标，而且第T-N帧图像、第T-(N-1)帧图像、...、第T-1帧图像、第T帧图像中最高温度点的温度均位于最高温度置信区间内。
可选地，若第T-(N-1)帧图像中最高温度点的温度未处于最高温度置信区间内，且第T-(N+1)帧图像中最高温度点的温度处于最高温度置信区间内，则当前帧之前的N帧图像为：第T-(N+1)帧图像、第T-N帧图像、第T-(N-2) 帧图像、...、第T-1帧图像、第T帧图像。下述的当前帧之前的K帧图像中最高温度点的温度位于最高温度置区间内也可以参见此处描述。
其中，确定帧图像中最高温度点的温度是否位于最高温度置信区间主要是通过判断该帧图像中最高温度点的温度以及该帧图像之前的K帧图像中最高温度点的温度之间的方差或者标准差是否小于预设值来实现。其中，若当前帧图像为第T帧图像，则当前帧之前的K帧图像为第T-K帧图像、第T-(K-1)帧图像、...、第T-1帧图像。
以判断当前帧图像中最高温度点的温度是否位于最高温度置信区间为例，其它帧图像类似，此处不再赘述。
判断该当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的方差是否小于预设值，若当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的方差小于预设值，则认为当前帧图像中最高温度点的温度处于最高温度置信区间内；若当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的方差大于或等于预设值，则认为当前帧图像中最高温度点的温度未处于最高温度置信区间内。或者，
判断该当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的标准差是否小于预设值，若当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的标准差小于预设值，则认为当前帧图像中最高温度点的温度处于最高温度置信区间内；若当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间(即K+1个温度)的标准差大于或等于预设值，则认为当前帧图像中最高温度点的温度未处于最高温度置信区间内。
其中，根据所述当前帧图像中最高温度点的第一坐标，以及所述红外相机感测的当前帧之前的N帧图像中最高温度点的第一坐标，确定所述期望坐标的实现方式可以包括如下几种，但本实施例并不限于此。
在一种可能的实现方式中，对当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧图像中最高温度点的第一坐标进行最小二乘法运算，获得 所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标(即这N+1个坐标)进行最小二乘法运算，将运算结果确定为期望坐标。
在另一种可能的实现方式中，根据当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧图像中最高温度点的第一坐标的平均值，确定所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标(即这N+1个坐标)的平均值确定为期望坐标。
在另一种可能的实现方式中，根据当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧图像中最高温度点的第一坐标的加权平均值，确定所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标(即这N+1个坐标)的加权平均值确定为期望坐标。
在一些实施例中，若当前帧图像中最高温度点的温度不位于最高温度置信区间时，则确定上一次确定的期望坐标为当前的期望坐标，即确定上一次确定的期望坐标为S302中所需确定的期望坐标。
图4为本发明另一实施例提供的最高温度点跟踪方法的流程图，如图4所示，本实施例的方法可以包括：
S401、获取红外相机感测的图像中最高温度点的第一坐标以及温度，所述图像为所述红外相机采集的图像。
本实施例中，S401的具体实现过程可以参见如图3所示实施例中的相关描述，此处不再赘述。
S402、根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标。
其中，S401与S402的执行顺序不分先后。
本实施例中，根据视觉追踪，可以确定红外相机采集的图像中预期最高 温度点，从而可以确定该预期最高温度点的坐标，其中，通过视觉追踪确定的预期最高温度点的坐标称为第二坐标。
在一些实施例中，在执行S402之前，还获取预期最高温度点的码流特征。相应地，S402的一种可能的实现方式可以包括：S4021和S4022。
S4021、获取所述红外相机采集的图像的红外码流。
S4022、根据所述码流特征对所述红外码流进行视觉追踪，确定所述第二坐标。
本实施例中，上述获取的预期最高温度点的码流特征可以是红外码流特征。本实施例可以获取图像的红外码流，该图像为红外相机采集的图像，然后根据上述预期最高温度点的码流特征，对该图像的红外码流进行视觉追踪，从而可以确定该图像中预期最高温度点的第二坐标。
其中，视觉追踪的具体实现过程可以参见现有技术中的相关描述，此处不再赘述。
其中，该码流特征可以是实时获取的，也可以是预先存储在存储器中的。
其中，实时获取码流特征的一种实现方式为：根据前M次确定的期望坐标对应的最高温度点的码流特征，确定预期最高温度点的码流特征，M为大于或等于1的整数。其中，在确定期望坐标之后，图像中该期望坐标对应的最高温度点的码流特征也可以获得，然后根据前M次确定的期望坐标对应的最高温度点的码流特征，确定当前的预期最高温度点的码流特征。
S403、根据所述最高温度点的温度、所述第一坐标以及所述预期最高温度点的第二坐标，确定最高温度点的期望坐标。
本实施例中，根据红外相机感测的最高温度点的温度，以及最高温度点的第一坐标以及通过视觉追踪获得的预期最高温度点的第二坐标，确定最高温度点的期望坐标。
在一些实施例中，上述S403的一种可能的实现方式为：以上述图像为当前帧图像为例，在获取到红外相机感测的当前帧图像中最高温度点的温度后，判断该红外相机感测的最高温度点的温度是否位于最高温度置信区间，如果该红外相机感测的最高温度点的温度位于该最高温度置信区内，则可以通过两种实现方案来确定期望坐标。
其中，一种方案为：根据所述红外相机感测的当前帧图像中最高温度点 的第一坐标以及所述当前帧图像中预期最高温度点的第二坐标，确定所述期望坐标。
其中，此方案的实现方式可以包括如下几种，但本实施例并不限于此。
在一种可能的实现方式中，对当前帧图像中最高温度点的第一坐标和该当前帧图像中预期最高温度点的第二坐标，进行最小二乘法运算，获得所述期望坐标。例如：将红外相机感测出的当前帧图像中最高温度点的坐标以及通过视觉跟踪获得的当前帧图像中预期温度点的坐标(即这两个坐标)进行最小二乘法运算，将运算结果确定为期望坐标。
在另一种可能的实现方式中，根据当前帧图像中最高温度点的第一坐标和该当前帧图像中预期最高温度点的第二坐标的平均值，确定所述期望坐标。例如：将红外相机感测出的当前帧图像中最高温度点的坐标以及通过视觉跟踪获得的当前帧图像中预期温度点的坐标(即这两个坐标)的平均值确定为期望坐标。
在另一种可能的实现方式中，当前帧图像中最高温度点的第一坐标和该当前帧图像中预期最高温度点的第二坐标的加权平均值，确定所述期望坐标。例如：将红外相机感测出的当前帧图像中最高温度点的坐标以及通过视觉跟踪获得的当前帧图像中预期温度点的坐标(即这两个坐标)的加权平均值确定为期望坐标。
其中，另一种方案为：根据所述当前帧图像中最高温度点的第一坐标和所述当前帧图像中预期最高温度点的第二坐标，以及当前帧之前的N帧图像中最高温度点的第一坐标和所述当前帧之前的N帧图像中预期最高温度点的第二坐标，确定所述期望坐标。其中，所述当前帧之前的N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
其中，此方案的实现方式可以包括如下几种，但本实施例并不限于此。
在一种可能的实现方式中，对当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧之前的N帧图像中预期最高温度点的第二坐标、当前帧图像中最高温度点的第一坐标和当前帧图像中预期最高温度点的第二坐标，进行最小二乘法运算，获得所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-N帧图像中预期温 度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-(N-1)帧图像中预期温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-1帧图像中预期温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T帧图像中预期温度点的坐标(即这2*(N+1)个坐标)进行最小二乘法运算，将运算结果确定为期望坐标。
在另一种可能的实现方式中，根据当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧之前的N帧图像中预期最高温度点的第二坐标、当前帧图像中最高温度点的第一坐标和当前帧图像中预期最高温度点的第二坐标的平均值，确定所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-N帧图像中预期温度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-(N-1)帧图像中预期温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-1帧图像中预期温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T帧图像中预期温度点的坐标(即这2*(N+1)个坐标)的平均值确定为期望坐标。
在另一种可能的实现方式中，根据当前帧之前的N帧图像中最高温度点的第一坐标以及当前帧之前的N帧图像中预期最高温度点的第二坐标、当前帧图像中最高温度点的第一坐标和当前帧图像中预期最高温度点的第二坐标的加权平均值，确定所述期望坐标。例如：将红外相机感测出的第T-N帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-N帧图像中预期温度点的坐标、红外相机感测出的第T-(N-1)帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-(N-1)帧图像中预期温度点的坐标、...、红外相机感测出的第T-1帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T-1帧图像中预期温度点的坐标、红外相机感测出的第T帧图像中最高温度点的坐标以及通过视觉跟踪获得的第T帧图像中预期温度点的坐标(即这2*(N+1)个坐标)的加权平均值确定为期望坐标。
其中，确定帧图像中最高温度点的温度是否位于最高温度置信区间可以是通过判断该帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高 温度点的温度之间的方差或者标准差是否小于预设值来实现。具体过程可以参见上述实施例中的描述，此处不再赘述。
在一些实施例中，若当前帧图像中最高温度点的温度不位于最高温度置信区间时，则确定上一次确定的期望坐标为当前的期望坐标，即确定上一次确定的期望坐标为S302中所需确定的期望坐标。
S404、根据所述期望坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度。
S405、根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
本实施例中，S404和S405的具体实现过程可以参见图3所示实施例的相关描述，此处不再赘述。
本实施例中，通过红外相机感测的帧图像中最高温度点的温度和坐标，以及通过视觉追踪获得帧图像中最高温度点的坐标，并根据上述参数来确定最高温度点的期望坐标更加接近实际的最高温度点，以保证下一帧图像中的最高温度点实时显示在图像的目标位置。
本发明实施例中还提供了一种计算机存储介质，该计算机存储介质中存储有程序指令，所述程序执行时可包括如图2-图4及其对应实施例中的最高温度点跟踪方法的部分或全部步骤。
图5为本发明一实施例提供的最高温度点跟踪装置的结构示意图，如图5所示，本实施例的最高温度点跟踪装置500可以包括：存储器501和处理器502。处理器502可以是中央处理单元(Central Processing Unit，CPU)，该处理器502还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
存储器501，用于存储程序指令；
所述处理器502，用于调用所述存储器501中存储的所述程序指令以实现：
获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红 外相机采集的图像；
根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度；
根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
在一些实施例中，所述处理器502，还用于：获取红外相机感测的图像中最高温度点的温度；
所述处理器502在根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度时，具体用于：根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标；以及根据所述期望坐标及所述图像中目标位置的坐标，确定所述云台的旋转角度。
在一些实施例中，所述处理器502，具体用于：
在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，确定所述当前帧图像中最高温度点的第一坐标为所述期望坐标；或者，
在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标，以及所述红外相机感测的当前帧之前的N帧图像中最高温度点的第一坐标，确定所述期望坐标；
其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
在一些实施例中，所述处理器502还用于在根据所述最高温度点的温度和第一坐标，确定最高温度点的期望坐标之前，根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标；
所述处理器502在根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标时，具体用于：根据所述最高温度点的温度、所述第一坐标以及所述预期最高温度点的第二坐标，确定最高温度点的期望坐标。
在一些实施例中，所述处理器502还用于在根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标之前，获取预期最高温度点的码流特征；
所述处理器502在根据视觉追踪，确定红外相机采集的图像中最高温度 点的第二坐标时，具体用于：获取所述红外相机采集的图像的红外码流；以及根据所述码流特征对所述红外码流进行视觉追踪，确定所述第二坐标。
在一些实施例中，所述处理器502，具体用于：根据前M次确定的期望坐标对应的最高温度点的码流特征，确定预期最高温度点的码流特征；所述M为大于或等于1的整数。
在一些实施例中，所述处理器502，具体用于：
在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述红外相机感测的当前帧图像中最高温度点的第一坐标以及所述当前帧图像中预期最高温度点的第二坐标，确定所述期望坐标；或者，
在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标和所述当前帧图像中预期最高温度点的第二坐标，以及当前帧之前的N帧图像中最高温度点的第一坐标和所述当前帧之前的N帧图像中预期最高温度点的第二坐标，确定所述期望坐标；
其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
在一些实施例中，所述处理器502，还用于在所述当前帧图像中最高温度点的温度不位于最高温度置信区间时，确定上一次确定的期望坐标为当前的期望坐标。
在一些实施例中，所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间，包括：
在所述当前帧图像中最高温度点的温度以及当前帧之前的K帧图像中最高温度点的温度之间的方差或者标准差小于预设值时，所述当前帧图像中最高温度点的温度位于最高温度置信区间；
其中，所述K帧图像为最高温度点的温度位于最高温度置信区间内的连续的K帧图像，所述K为大于或等于1的整数。
在一些实施例中，所述处理器502，具体用于：
对所述至少两个坐标进行最小二乘法运算，获得所述期望坐标；或者，
根据所述至少两个坐标的平均值，确定所述期望坐标；或者，
根据所述至少两个坐标的加权平均值，确定所述期望坐标；
其中，所述至少两个坐标包括至少两个第一坐标，或者，所述至少两个 坐标包括至少一个第一坐标和至少一个第二坐标。
在一些实施例中，所述目标位置为所述图像的正中心。
本实施例的装置，可以用于执行本发明上述各方法实施例的技术方案，其实现原理和技术效果类似，此处不再赘述。
图6为本发明另一实施例提供的最高温度点跟踪装置的结构示意图，如图6所示，本实施例的最高温度点跟踪装置500在图5所示实施例的基础上，还可以包括：显示界面503。
显示界面503，用于在所述处理器502根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置之后，显示所述红外相机采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。
本实施例的装置，可以用于执行本发明上述各方法实施例的技术方案，其实现原理和技术效果类似，此处不再赘述。
图7为本发明一实施例提供的无人机的结构示意图，如图7所示，本实施例的无人机1000包括：最高温度点跟踪装置500、机体600、云台700和红外相机800。所述云台700与所述机体600连接；所述云台700用于搭载所述红外相机800。所述最高温度点跟踪装置500分别与所述云台700和所述红外相机800通信连接。
其中，所述最高温度点跟踪装置500可以采用图5或图6所示实施例的结构，其对应地，可以执行本发明上述各方法实施例的技术方案，其实现原理和技术效果类似，此处不再赘述。
图8为本发明另一实施例提供的无人机的结构示意图，如图8所示，本实施例的无人机1000在图7所示实施例的基础上还可以包括：显示装置900；其中，所述显示装置900与所述红外相机800通信连接；
所述显示装置900，用于显示所述红外相机800采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。
需要说明的是，该最高温度点跟踪装置500可以属于无人机1000的飞行控制***的一部分，或者，该最高温度点跟踪装置500属于无人机1000地面端的控制设备的一部分。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤 可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：只读内存(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (26)

  1. 一种最高温度点跟踪方法，其特征在于，包括：
    获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红外相机采集的图像；
    根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度；
    根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    获取红外相机感测的图像中最高温度点的温度；
    所述根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度，包括：
    根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标；
    根据所述期望坐标及所述图像中目标位置的坐标，确定所述云台的旋转角度。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述最高温度点的温度和第一坐标，确定最高温度点的期望坐标，包括：
    在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，确定所述当前帧图像中最高温度点的第一坐标为所述期望坐标；或者，
    在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标，以及所述红外相机感测的所述当前帧之前的N帧图像中最高温度点的第一坐标，确定所述期望坐标；
    其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
  4. 根据权利要求2所述的方法，其特征在于，所述根据所述最高温度点的温度和第一坐标，确定最高温度点的期望坐标之前，还包括：
    根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标；
    所述根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期 望坐标，包括：
    根据所述最高温度点的温度、所述第一坐标以及所述预期最高温度点的第二坐标，确定最高温度点的期望坐标。
  5. 根据权利要求4所述的方法，其特征在于，所述根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标之前，还包括：
    获取预期最高温度点的码流特征；
    所述根据视觉追踪，确定红外相机采集的图像中最高温度点的第二坐标，包括：
    获取所述红外相机采集的图像的红外码流；
    根据所述码流特征对所述红外码流进行视觉追踪，确定所述第二坐标。
  6. 根据权利要求5所述的方法，其特征在于，所述获取预期最高温度点的码流特征，包括：
    根据前M次确定的期望坐标对应的最高温度点的码流特征，确定预期最高温度点的码流特征；所述M为大于或等于1的整数。
  7. 根据权利要求4-6任意一项所述的方法，其特征在于，所述根据所述最高温度点的温度、所述第一坐标以及所述预期最高温度点的第二坐标，确定最高温度点的期望坐标，包括：
    在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述红外相机感测的当前帧图像中最高温度点的第一坐标以及所述当前帧图像中预期最高温度点的第二坐标，确定所述期望坐标；或者，
    在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标和所述当前帧图像中预期最高温度点的第二坐标，以及所述当前帧之前的N帧图像中最高温度点的第一坐标和所述当前帧之前的N帧图像中预期最高温度点的第二坐标，确定所述期望坐标；
    其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
  8. 根据权利要求3或7所述的方法，其特征在于，还包括：
    在所述当前帧图像中最高温度点的温度不位于最高温度置信区间时，确定上一次确定的期望坐标为当前的期望坐标。
  9. 根据权利要求3或7或8所述的方法，其特征在于，所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间，包括：
    在所述当前帧图像中最高温度点的温度以及所述当前帧之前的K帧图像中最高温度点的温度之间的方差或者标准差小于预设值时，所述当前帧图像中最高温度点的温度位于最高温度置信区间；
    所述K帧图像为最高温度点的温度位于最高温度置信区间内的连续的K帧图像，所述K为大于或等于1的整数。
  10. 根据权利要求3或7-9任意一项所述的方法，其特征在于，根据至少两个坐标，确定期望坐标，包括：
    对所述至少两个坐标进行最小二乘法运算，获得所述期望坐标；或者，
    根据所述至少两个坐标的平均值，确定所述期望坐标；或者，
    根据所述至少两个坐标的加权平均值，确定所述期望坐标；
    其中，所述至少两个坐标包括至少两个第一坐标，或者，所述至少两个坐标包括至少一个第一坐标和至少一个第二坐标。
  11. 根据权利要求1-10任意一项所述的方法，其特征在于，所述根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置之后，还包括：
    在显示界面显示所述红外相机采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。
  12. 根据权利要求1-11任意一项所述的方法，其特征在于，所述目标位置为所述图像的正中心。
  13. 一种最高温度点跟踪装置，其特征在于，包括：存储器和处理器；
    所述存储器，用于存储程序指令；
    所述处理器，用于调用所述存储器中存储的所述程序指令以实现：
    获取红外相机感测的图像中最高温度点的第一坐标；所述图像为所述红外相机采集的图像；
    根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度；
    根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置。
  14. 根据权利要求13所述的装置，其特征在于，所述处理器，还用于：获取红外相机感测的图像中最高温度点的温度；
    所述处理器在根据所述最高温度点的第一坐标及所述图像中目标位置的坐标，确定搭载所述红外相机的云台的旋转角度时，具体用于：根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标；以及根据所述期望坐标及所述图像中目标位置的坐标，确定所述云台的旋转角度。
  15. 根据权利要求14所述的装置，其特征在于，所述处理器，具体用于：
    在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，确定所述当前帧图像中最高温度点的第一坐标为所述期望坐标；或者，
    在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标，以及所述红外相机感测的所述当前帧之前的N帧图像中最高温度点的第一坐标，确定所述期望坐标；
    其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
  16. 根据权利要求14所述的装置，其特征在于，所述处理器还用于在根据所述最高温度点的温度和第一坐标，确定最高温度点的期望坐标之前，根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标；
    所述处理器在根据所述最高温度点的温度和所述第一坐标，确定最高温度点的期望坐标时，具体用于：根据所述最高温度点的温度、所述第一坐标以及所述预期最高温度点的第二坐标，确定最高温度点的期望坐标。
  17. 根据权利要求16所述的装置，其特征在于，所述处理器还用于在根据视觉追踪，确定红外相机采集的图像中预期最高温度点的第二坐标之前，获取预期最高温度点的码流特征；
    所述处理器在根据视觉追踪，确定红外相机采集的图像中最高温度点的第二坐标时，具体用于：获取所述红外相机采集的图像的红外码流；以及根据所述码流特征对所述红外码流进行视觉追踪，确定所述第二坐标。
  18. 根据权利要求17所述的装置，其特征在于，所述处理器，具体用于：根据前M次确定的期望坐标对应的最高温度点的码流特征，确定预期最高温度点的码流特征；所述M为大于或等于1的整数。
  19. 根据权利要求16-18任意一项所述的装置，其特征在于，所述处理器，具体用于：
    在所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述红外相机感测的当前帧图像中最高温度点的第一坐标以及所述当前帧图像中预期最高温度点的第二坐标，确定所述期望坐标；或者，
    在所述当前帧图像中最高温度点的温度位于最高温度置信区间时，根据所述当前帧图像中最高温度点的第一坐标和所述当前帧图像中预期最高温度点的第二坐标，以及所述当前帧之前的N帧图像中最高温度点的第一坐标和所述当前帧之前的N帧图像中预期最高温度点的第二坐标，确定所述期望坐标；
    其中，所述N帧图像为最高温度点的温度位于最高温度置信区间内的连续的N帧图像，所述N为大于或等于1的整数。
  20. 根据权利要求15或19所述的装置，其特征在于，所述处理器，还用于在所述当前帧图像中最高温度点的温度不位于最高温度置信区间时，确定上一次确定的期望坐标为当前的期望坐标。
  21. 根据权利要求15或19或20所述的装置，其特征在于，所述红外相机感测的当前帧图像中最高温度点的温度位于最高温度置信区间，包括：
    在所述当前帧图像中最高温度点的温度以及所述当前帧之前的K帧图像中最高温度点的温度之间的方差或者标准差小于预设值时，所述当前帧图像中最高温度点的温度位于最高温度置信区间；
    其中，所述K帧图像为最高温度点的温度位于最高温度置信区间内的连续的K帧图像，所述K为大于或等于1的整数。
  22. 根据权利要求15或17-21任意一项所述的装置，其特征在于，所述处理器，具体用于：
    对所述至少两个坐标进行最小二乘法运算，获得所述期望坐标；或者，
    根据所述至少两个坐标的平均值，确定所述期望坐标；或者，
    根据所述至少两个坐标的加权平均值，确定所述期望坐标；
    其中，所述至少两个坐标包括至少两个第一坐标，或者，所述至少两个坐标包括至少一个第一坐标和至少一个第二坐标。
  23. 根据权利要求13-22任意一项所述的装置，其特征在于，所述目标 位置为所述图像的正中心。
  24. 根据权利要求13-23任意一项所述的装置，其特征在于，还包括：
    显示界面，用于在所述处理器根据所述旋转角度，控制所述云台旋转以调整所述红外相机采集的图像中最高温度点位于所述目标位置之后，显示所述红外相机采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。
  25. 一种无人机，其特征在于，包括：机体、云台、红外相机以及如权利要求13-23任意一项所述的最高温度点跟踪装置；所述云台与所述机体连接；所述云台用于搭载所述红外相机；
    所述最高温度点跟踪装置分别与所述云台和所述红外相机通信连接。
  26. 根据权利要求25所述的无人机，其特征在于，还包括：显示装置；所述显示装置与所述红外相机通信连接；
    所述显示装置，用于显示所述红外相机采集的图像，其中，所述图像中最高温度点位于所述图像的所述目标位置。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113834572A (zh) * 2021-08-26 2021-12-24 电子科技大学 一种无人机非制冷型热像仪测温结果漂移去除方法

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110141816A (zh) * 2019-04-23 2019-08-20 上海中备实业公司 一种用于消防车的智能灭火设备和灭火方法
CN110824295B (zh) * 2019-10-22 2021-08-31 广东电网有限责任公司 一种基于三维图形的红外热像故障定位方法
CN112154450A (zh) * 2019-11-13 2020-12-29 深圳市大疆创新科技有限公司 识别方法、测温方法、设备及存储介质
CN111678558A (zh) * 2020-07-31 2020-09-18 国网四川省电力公司成都供电公司 一种应用于充油设备的红外热成像油位、温度监测***及方法
CN112489348A (zh) * 2020-11-12 2021-03-12 华能新华发电有限责任公司 一种基于无人机的煤场温度智能检测预警方法

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101046908A (zh) * 2007-05-08 2007-10-03 中国科学院上海技术物理研究所 基于红外相机的森林火情动态监测报警***
CN106297142A (zh) * 2016-08-17 2017-01-04 云南电网有限责任公司电力科学研究院 一种无人机山火勘探控制方法及***
CN106558181A (zh) * 2015-09-28 2017-04-05 东莞前沿技术研究院 火灾监测方法和装置

Family Cites Families (68)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4189747A (en) * 1967-09-15 1980-02-19 Hughes Aircraft Company Infrared tracking system
US5062586A (en) * 1990-05-17 1991-11-05 Electronics & Space Corporation Missile tracking, guidance and control apparatus
DE4135260C1 (zh) * 1991-10-25 1993-02-25 Bodenseewerk Geraetetechnik Gmbh, 7770 Ueberlingen, De
US5342051A (en) * 1992-10-30 1994-08-30 Accu-Sport International, Inc. Apparatus and method for tracking the flight of a golf ball
JP3346189B2 (ja) * 1996-10-24 2002-11-18 トヨタ自動車株式会社 車両運動量検出装置
US5960097A (en) * 1997-01-21 1999-09-28 Raytheon Company Background adaptive target detection and tracking with multiple observation and processing stages
US5918305A (en) * 1997-08-27 1999-06-29 Trw Inc. Imaging self-referencing tracker and associated methodology
DE19756763A1 (de) * 1997-12-19 1999-06-24 Bodenseewerk Geraetetech Suchkopf für zielverfolgende Flugkörper
CA2534587A1 (en) * 2003-08-05 2005-03-03 University Of Hawai'i Microwave self-phasing antenna arrays for secure data transmission & satellite network crosslinks
CN101622630B (zh) * 2005-01-07 2012-07-04 高通股份有限公司 检测和跟踪图像中的物体
FR2895924B1 (fr) * 2006-01-10 2009-09-25 Valeo Electronique Sys Liaison Procede de brasage entre eux d'au moins deux organes empiles
CA2546758C (en) * 2006-05-12 2009-07-07 Alberta Research Council Inc. A system and a method for detecting a damaged or missing machine part
JP4709101B2 (ja) * 2006-09-01 2011-06-22 キヤノン株式会社 自動追尾カメラ装置
US20100157056A1 (en) * 2007-05-20 2010-06-24 Rafael Advanced Defense Systems Ltd. Tracking and imaging data fusion
US8199198B2 (en) * 2007-07-18 2012-06-12 Delphi Technologies, Inc. Bright spot detection and classification method for a vehicular night-time video imaging system
WO2009049272A2 (en) * 2007-10-10 2009-04-16 Gerard Dirk Smits Image projector with reflected light tracking
US8946606B1 (en) * 2008-03-26 2015-02-03 Arete Associates Determining angular rate for line-of-sight to a moving object, with a body-fixed imaging sensor
US9310191B1 (en) * 2008-07-08 2016-04-12 Bae Systems Information And Electronic Systems Integration Inc. Non-adjustable pointer-tracker gimbal used for directed infrared countermeasures systems
CN101419055B (zh) * 2008-10-30 2010-08-25 北京航空航天大学 基于视觉的空间目标位姿测量装置和方法
US8294560B2 (en) * 2009-07-20 2012-10-23 The United States Of America As Represented By The Secretary Of The Army Method and apparatus for identifying threats using multiple sensors in a graphical user interface
US8116527B2 (en) * 2009-10-07 2012-02-14 The United States Of America As Represented By The Secretary Of The Army Using video-based imagery for automated detection, tracking, and counting of moving objects, in particular those objects having image characteristics similar to background
IL201682A0 (en) * 2009-10-22 2010-11-30 Bluebird Aero Systems Ltd Imaging system for uav
US10178290B2 (en) * 2010-02-17 2019-01-08 Sri International Method and apparatus for automatically acquiring facial, ocular, and iris images from moving subjects at long-range
US20110304737A1 (en) * 2010-06-15 2011-12-15 Flir Systems, Inc. Gimbal positioning with target velocity compensation
EP2474808A1 (de) * 2011-01-10 2012-07-11 Leica Geosystems AG Geodätisches Vermessungsgerät mit thermographischer Kamera
CN102182137A (zh) * 2011-02-25 2011-09-14 广州飒特电力红外技术有限公司 路面缺陷检测***及方法
US9930298B2 (en) * 2011-04-19 2018-03-27 JoeBen Bevirt Tracking of dynamic object of interest and active stabilization of an autonomous airborne platform mounted camera
TW201249713A (en) * 2011-06-02 2012-12-16 Hon Hai Prec Ind Co Ltd Unmanned aerial vehicle control system and method
CN102280005B (zh) * 2011-06-09 2014-10-29 广州飒特红外股份有限公司 基于红外热成像技术的森林防火预警***及方法
US20130021475A1 (en) * 2011-07-21 2013-01-24 Canant Ross L Systems and methods for sensor control
US9000371B2 (en) * 2011-08-26 2015-04-07 Custom Scene Technology, Inc. Camera, computer program and method for measuring thermal radiation and thermal rates of change
KR101339405B1 (ko) * 2012-03-19 2013-12-09 주식회사 팔콘 실시간 화재감지 및 화재정보전달 방법
CN102831620B (zh) * 2012-08-03 2015-09-30 南京理工大学 基于多假设跟踪数据关联的红外弱小目标搜索跟踪方法
US20170073070A1 (en) * 2013-02-06 2017-03-16 Zhou Tian Xing Amphibious vertical takeoff and landing unmanned device with artificial intelligence (AI) and method and system for managing a crisis environment and controlling one or more targets
US9065985B2 (en) * 2013-03-15 2015-06-23 Tolo, Inc. Diagonal collection of oblique imagery
US9070289B2 (en) * 2013-05-10 2015-06-30 Palo Alto Research Incorporated System and method for detecting, tracking and estimating the speed of vehicles from a mobile platform
US9025825B2 (en) * 2013-05-10 2015-05-05 Palo Alto Research Center Incorporated System and method for visual motion based object segmentation and tracking
US9678506B2 (en) * 2014-06-19 2017-06-13 Skydio, Inc. Magic wand interface and other user interaction paradigms for a flying digital assistant
US9603527B2 (en) * 2014-07-31 2017-03-28 Chung Hua University Person positioning and health care monitoring system
US10095942B2 (en) * 2014-12-15 2018-10-09 Reflex Robotics, Inc Vision based real-time object tracking system for robotic gimbal control
US20160214713A1 (en) * 2014-12-19 2016-07-28 Brandon Cragg Unmanned aerial vehicle with lights, audio and video
WO2016101155A1 (en) * 2014-12-23 2016-06-30 SZ DJI Technology Co., Ltd. Uav panoramic imaging
CN204822071U (zh) * 2015-07-03 2015-12-02 广西大学 多功能共轴双旋翼四轴飞行器
CN105049733B (zh) * 2015-08-28 2018-08-28 罗永进 一种定位拍摄辅助装置及方法
EP3353706A4 (en) * 2015-09-15 2019-05-08 SZ DJI Technology Co., Ltd. SYSTEM AND METHOD FOR MONITORING UNIFORM TARGET TRACKING
CN107003386B (zh) * 2015-10-20 2019-06-28 深圳市大疆创新科技有限公司 一种卫星导航测姿方法和装置及无人机
CN105212418A (zh) * 2015-11-05 2016-01-06 北京航天泰坦科技股份有限公司 基于红外夜视功能的增强现实智能头盔研制
CN205177061U (zh) * 2015-11-14 2016-04-20 深圳市易特科信息技术有限公司 用于火灾救援的无人机预警***
CN105718895A (zh) * 2016-01-22 2016-06-29 张健敏 一种基于视觉特征的无人机
US9804293B1 (en) * 2016-04-13 2017-10-31 Northrop Grumman Systems Corporation UAVs for the detection and tracking of intense tornadoes
CN106197422B (zh) * 2016-06-27 2019-09-03 东南大学 一种基于二维标签的无人机定位及目标跟踪方法
US10636150B2 (en) * 2016-07-21 2020-04-28 Gopro, Inc. Subject tracking systems for a movable imaging system
US20180204331A1 (en) * 2016-07-21 2018-07-19 Gopro, Inc. Subject tracking systems for a movable imaging system
US10520943B2 (en) * 2016-08-12 2019-12-31 Skydio, Inc. Unmanned aerial image capture platform
US10514711B2 (en) * 2016-10-09 2019-12-24 Airspace Systems, Inc. Flight control using computer vision
JP6478177B2 (ja) * 2016-11-18 2019-03-06 エスゼット ディージェイアイ テクノロジー カンパニー リミテッドＳｚ Ｄｊｉ Ｔｅｃｈｎｏｌｏｇｙ Ｃｏ．，Ｌｔｄ 制御装置、撮像システム、移動体、制御方法、およびプログラム
US10269133B2 (en) * 2017-01-03 2019-04-23 Qualcomm Incorporated Capturing images of a game by an unmanned autonomous vehicle
US10599161B2 (en) * 2017-08-08 2020-03-24 Skydio, Inc. Image space motion planning of an autonomous vehicle
IL254460B2 (en) * 2017-09-12 2024-01-01 Israel Aerospace Ind Ltd Active household head
US10809064B2 (en) * 2018-02-08 2020-10-20 Raytheon Company Image geo-registration for absolute navigation aiding using uncertainy information from the on-board navigation system
US10996683B2 (en) * 2018-02-09 2021-05-04 Skydio, Inc. Aerial vehicle touchdown detection
US11205274B2 (en) * 2018-04-03 2021-12-21 Altumview Systems Inc. High-performance visual object tracking for embedded vision systems
US11740630B2 (en) * 2018-06-12 2023-08-29 Skydio, Inc. Fitness and sports applications for an autonomous unmanned aerial vehicle
US11749124B2 (en) * 2018-06-12 2023-09-05 Skydio, Inc. User interaction with an autonomous unmanned aerial vehicle
US10679054B2 (en) * 2018-09-04 2020-06-09 International Business Machines Corporation Object cognitive identification solution
US11697497B2 (en) * 2018-10-03 2023-07-11 Sarcos Corp. Aerial vehicles having countermeasures deployed from a platform for neutralizing target aerial vehicles
US11472550B2 (en) * 2018-10-03 2022-10-18 Sarcos Corp. Close proximity countermeasures for neutralizing target aerial vehicles
US11440656B2 (en) * 2018-10-03 2022-09-13 Sarcos Corp. Countermeasure deployment system facilitating neutralization of target aerial vehicles

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101046908A (zh) * 2007-05-08 2007-10-03 中国科学院上海技术物理研究所 基于红外相机的森林火情动态监测报警***
CN106558181A (zh) * 2015-09-28 2017-04-05 东莞前沿技术研究院 火灾监测方法和装置
CN106297142A (zh) * 2016-08-17 2017-01-04 云南电网有限责任公司电力科学研究院 一种无人机山火勘探控制方法及***

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113834572A (zh) * 2021-08-26 2021-12-24 电子科技大学 一种无人机非制冷型热像仪测温结果漂移去除方法
CN113834572B (zh) * 2021-08-26 2023-05-12 电子科技大学 一种无人机非制冷型热像仪测温结果漂移去除方法

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