SG150527A1 - Method and system for multi-object tracking - Google Patents

Method and system for multi-object tracking

Info

Publication number
SG150527A1
SG150527A1 SG200901121-4A SG2009011214A SG150527A1 SG 150527 A1 SG150527 A1 SG 150527A1 SG 2009011214 A SG2009011214 A SG 2009011214A SG 150527 A1 SG150527 A1 SG 150527A1
Authority
SG
Singapore
Prior art keywords
child node
objects
child
image
node
Prior art date
Application number
SG200901121-4A
Inventor
Li Liyuan
Luo Ruijiang
Ma Ruihua
Leman Karianto
Kumar Pankaj
Lee Beng Hai
Huang Welmin
Original Assignee
Agency Science Tech & Res
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Agency Science Tech & Res filed Critical Agency Science Tech & Res
Publication of SG150527A1 publication Critical patent/SG150527A1/en

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/174—Segmentation; Edge detection involving the use of two or more images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/194—Segmentation; Edge detection involving foreground-background segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/254—Analysis of motion involving subtraction of images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/24—Aligning, centring, orientation detection or correction of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/62—Extraction of image or video features relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • Image Analysis (AREA)

Abstract

Method And System For Multi-Object Tracking A method and system for multi-object tracking in a video signal. The method comprises the steps of receiving first and second segmented images of two consecutive frames of the video signal respectively, at least one of the first and second segmented images including one or more foreground regions, each foreground region corresponding to one or more objects to be tracked; generating one or more directed acyclic graphs (DAGs) for zero or more parent nodes in the first segmented image and zero to more child nodes in the second segmented images, each DAG including at least one parent or child node; and for each parent node having two or more child nodes, a) sorting the corresponding objects of the foreground region contributing to said each parent node according to estimated depth in said first image; b) assigning the corresponding object having the lowest depth to one of the child nodes of said each parent node; c) removing a visual content of the assigned corresponding object from the visual data associated with said one child node; and iterating steps b) to c) in order of increasing depth of the corresponding objects for assigning all corresponding objects to the two or more child nodes; and then for each child node having only one corresponding object assigned thereto, update a state and the visual content of said one object based on the second image; for each child node having two or more corresponding objects assigned thereto, d) sorting the corresponding objects according to estimated depth in said each child node in said second image; e) applying a means-shift calculation to locate the corresponding object having the lowest depth in said each child node; f) updating the state and the visual content of the located corresponding object based on the second image; g) removing the updated visual content of the located corresponding object from the visual data associated with said each child node; and iterating steps e) to g) in order of increasing depth of the corresponding objects for locating all corresponding objects in a corresponding region of said each child node.
SG200901121-4A 2006-07-11 2007-07-11 Method and system for multi-object tracking SG150527A1 (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US80696406P 2006-07-11 2006-07-11

Publications (1)

Publication Number Publication Date
SG150527A1 true SG150527A1 (en) 2009-03-30

Family

ID=38923513

Family Applications (1)

Application Number Title Priority Date Filing Date
SG200901121-4A SG150527A1 (en) 2006-07-11 2007-07-11 Method and system for multi-object tracking

Country Status (2)

Country Link
SG (1) SG150527A1 (en)
WO (2) WO2008008046A1 (en)

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US8572740B2 (en) 2009-10-01 2013-10-29 Kaspersky Lab, Zao Method and system for detection of previously unknown malware
US8483481B2 (en) 2010-07-27 2013-07-09 International Business Machines Corporation Foreground analysis based on tracking information
WO2014038924A2 (en) * 2012-09-06 2014-03-13 Mimos Berhad A method for producing a background model
AU2013242830B2 (en) * 2013-10-10 2016-11-24 Canon Kabushiki Kaisha A method for improving tracking in crowded situations using rival compensation
CN103729861B (en) * 2014-01-03 2016-06-22 天津大学 A kind of multi-object tracking method
KR101631955B1 (en) 2014-12-10 2016-06-20 삼성전자주식회사 Target object tracking apparatus and method of operations thereof
EP3246874B1 (en) * 2016-05-16 2018-03-14 Axis AB Method and apparatus for updating a background model used for background subtraction of an image
GB2550858A (en) 2016-05-26 2017-12-06 Nokia Technologies Oy A method, an apparatus and a computer program product for video object segmentation
US10360456B2 (en) * 2016-08-12 2019-07-23 Qualcomm Incorporated Methods and systems of maintaining lost object trackers in video analytics
CN107368784A (en) * 2017-06-15 2017-11-21 西安理工大学 A kind of novel background subtraction moving target detecting method based on wavelet blocks
US10304207B2 (en) * 2017-07-07 2019-05-28 Samsung Electronics Co., Ltd. System and method for optical tracking
CN108399411B (en) * 2018-02-26 2019-07-05 北京三快在线科技有限公司 A kind of multi-cam recognition methods and device
CN109143222B (en) * 2018-07-27 2023-04-25 中国科学院半导体研究所 Three-dimensional maneuvering target tracking method based on divide-and-conquer sampling particle filtering
CN111179304B (en) * 2018-11-09 2024-04-05 北京京东尚科信息技术有限公司 Target association method, apparatus and computer readable storage medium
CN110121034B (en) * 2019-05-09 2021-09-07 腾讯科技（深圳）有限公司 Method, device, equipment and storage medium for implanting information into video
CN112395920B (en) 2019-08-16 2024-03-19 富士通株式会社 Gesture recognition device and method based on radar and electronic equipment
CN110889864B (en) * 2019-09-03 2023-04-18 河南理工大学 Target tracking method based on double-layer depth feature perception
CN112991382B (en) * 2019-12-02 2024-04-09 中国科学院国家空间科学中心 Heterogeneous visual target tracking system and method based on PYNQ framework
CN111178218B (en) * 2019-12-23 2023-07-04 北京中广上洋科技股份有限公司 Multi-feature joint video tracking method and system based on face recognition
CN111340846B (en) * 2020-02-25 2023-02-17 重庆邮电大学 Multi-feature fusion anti-occlusion target tracking method
CN111726264B (en) * 2020-06-18 2021-11-19 中国电子科技集团公司第三十六研究所 Network protocol variation detection method, device, electronic equipment and storage medium
CN117953015B (en) * 2024-03-26 2024-07-09 武汉工程大学 Multi-row person tracking method, system, equipment and medium based on video super-resolution

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US6542621B1 (en) * 1998-08-31 2003-04-01 Texas Instruments Incorporated Method of dealing with occlusion when tracking multiple objects and people in video sequences
US6879705B1 (en) * 1999-07-14 2005-04-12 Sarnoff Corporation Method and apparatus for tracking multiple objects in a video sequence
US6826292B1 (en) * 2000-06-23 2004-11-30 Sarnoff Corporation Method and apparatus for tracking moving objects in a sequence of two-dimensional images using a dynamic layered representation
IL141650A (en) * 2001-02-26 2005-12-18 Elop Electrooptics Ind Ltd Method and system for tracking an object
WO2005036456A2 (en) * 2003-05-12 2005-04-21 Princeton University Method and apparatus for foreground segmentation of video sequences
US7224735B2 (en) * 2003-05-21 2007-05-29 Mitsubishi Electronic Research Laboratories, Inc. Adaptive background image updating
JP4444583B2 (en) * 2003-05-21 2010-03-31 富士通株式会社 Object detection apparatus and program

Also Published As

Publication number Publication date
WO2008008046A1 (en) 2008-01-17
WO2008008045A1 (en) 2008-01-17

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