CN110910512A - Virtual object self-adaptive adjusting method and device, computer equipment and storage medium - Google Patents
Virtual object self-adaptive adjusting method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The disclosure relates to a virtual object adaptive adjustment method, a virtual object adaptive adjustment device, a computer device and a storage medium, wherein the method comprises the following steps: the method comprises the steps of identifying a video frame containing a target object to obtain key point information, zooming information and contour information of the target object, generating a virtual object according to the contour information, obtaining key point information of a standard object corresponding to the target object, obtaining target magnification for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object, and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information. By the method, the position and the size of the virtual object on the target object can be adjusted according to the target magnification and the zooming information, so that the virtual object is attached to the real image.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a method and an apparatus for adaptively adjusting a virtual object, a computer device, and a storage medium.
Background
In recent years, with the development of AR technology, many scenes need to add a virtual object to a live image, for example, add a virtual decoration to a human face, and the implementation method generally uses a human face recognition algorithm to obtain scaling information of the human face and render the virtual decoration to the live image according to the same size. However, the method can cause the virtual ornament and the real face not to be attached to each other, and particularly, under the condition that the virtual ornament is far away from the center of the face, the virtual ornament is too close to the center of the face or far away from the center of the face due to the fact that the face is too fat or too long, so that the effect is not really matched, and the virtual object and the real image are not attached to each other.
Therefore, the related art has a problem that the virtual object and the live image do not adhere to each other in the AR scene.
Disclosure of Invention
The present disclosure provides a virtual object adaptive adjustment method, apparatus, computer device, and storage medium, to at least solve the problem in the related art that a virtual object and a live image do not fit together in an AR scene.
The technical scheme of the disclosure is as follows:
according to a first aspect of the embodiments of the present disclosure, there is provided a virtual object adaptive adjustment method, including:
identifying a video frame containing a target object to obtain key point information, zooming information and outline information of the target object;
generating a virtual object according to the contour information;
acquiring key point information of a standard object corresponding to the target object;
obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
According to a second aspect of the embodiments of the present disclosure, there is provided a virtual object adaptive adjustment apparatus, including:
the identification module is used for identifying the video frame containing the target object to obtain key point information, zooming information and outline information of the target object;
the generating module is used for generating a virtual object according to the contour information;
the key point acquisition module is used for acquiring key point information of a standard object corresponding to the target object;
the multiplying power acquisition module is used for obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and the adjusting module is used for adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
According to a third aspect of embodiments of the present disclosure, there is provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect when executing the computer program.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method of the first aspect.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:
the method comprises the steps of identifying a video frame containing a target object to obtain key point information, zooming information and contour information of the target object, generating a virtual object according to the contour information, obtaining key point information of a standard object corresponding to the target object, obtaining target magnification for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object, and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information. By the method, the position and the size of the virtual object on the target object can be adjusted according to the target magnification and the zooming information, so that the virtual object is attached to the real image.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
Fig. 1 is an application environment diagram illustrating a virtual object adaptive adjustment method according to an exemplary embodiment.
Fig. 2 is a flowchart illustrating a virtual object adaptive adjustment method according to an exemplary embodiment.
FIG. 3 is a flowchart of the refinement step of step S24 in accordance with an exemplary embodiment.
Fig. 4 is a flowchart of the refinement step of step S243 in an exemplary embodiment.
Fig. 5 is a flowchart illustrating a virtual object adaptive adjustment method according to an exemplary embodiment.
Fig. 6 is a block diagram illustrating a virtual object adaptive adjustment apparatus according to an exemplary embodiment.
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The virtual object adaptive adjustment method provided by the present disclosure can be applied to the application environment shown in fig. 1. The virtual object adaptive adjusting device comprises an image acquisition device 11 and a computer device 12 which are connected. The image capturing device 11 and the computer device 12 may be configured as an integrated terminal, which may include, but is not limited to, various personal computers, notebook computers, smart phones, and tablet computers. The image capturing device 11 and the computer device 12 may also be an image capturing device 11 (e.g. a camera) and a server, which are respectively and independently arranged, the image capturing device 11 is communicatively connected to the server through a network, and the server may be implemented by an independent server or a server cluster composed of a plurality of servers.
Alternatively, the image capturing device 11 captures an image or a video (i.e., a video frame containing the target object), and the video frame may be an image captured by the image capturing device 11 from a network or other image capturing devices 11, or an image captured by the image capturing device 11 from a video frame, or the like. After acquiring the video frame containing the target object, the image capture device 11 sends the video frame containing the target object to the computer device 12. Optionally, the computer device 12 comprises at least one processor 121 and a memory 122. Alternatively, the processor 121 may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), and the like, and the processor 121 may be a multi-core processor, such as a multi-core GPU.
The memory 122 in the computer device 12 stores a virtual object adaptive adjustment algorithm, the processor 121 may call and run the virtual object adaptive adjustment algorithm in the memory 122, identify a video frame including a target object, obtain key point information, scaling information, and contour information of the target object, generate a virtual object according to the contour information, obtain key point information of a standard object corresponding to the target object, obtain a target magnification for adaptive adjustment according to the virtual object, the key point information of the target object, and the key point information of the standard object, and adjust a position and a size of the virtual object on the target object according to the target magnification and the scaling information.
Fig. 2 is a flowchart illustrating a virtual object adaptive adjustment method according to an exemplary embodiment, and as shown in fig. 2, a virtual object adaptive adjustment method is used in fig. 1, and includes the following steps:
in step S21, the video frame including the target object is identified, and the key point information, the zoom information, and the contour information of the target object are obtained.
The target object may be a person, an animal, or other object having mobility, or may be a still object such as a table or a cabinet.
The key point information is a set including information such as key point positions of the target object, and may include eyes, eyebrows, a nose, a mouth, cheeks, a face center point, and the like, assuming that the target object is a human face.
Wherein the zoom information is information of a zoom magnification determined from pixel information in the video frame.
Wherein the contour information refers to line features constituting the outer edge of the target object.
In the embodiment of the present disclosure, identifying a video frame including a target object to obtain key point information, scaling information, and contour information of the target object belongs to the prior art, and is not described herein again.
In step S22, a virtual object is generated from the contour information.
The virtual object may be a two-dimensional planar object or a three-dimensional stereoscopic object.
In the disclosed embodiment, the virtual object is rendered in accordance with the contour information.
In step S23, the key point information of the standard object corresponding to the target object is acquired.
In the embodiment of the present disclosure, several standard objects are stored in advance, and the standard objects are objects that are set and stored in advance and play a comparison role. The standard objects include people, animals, tables, cabinets and the like, and each standard object also has respective key point information. Assuming that the target object is a person, the standard object will also be a person, and assuming that the target object is a table, the standard object will also be a table.
In step S24, a target magnification for adaptive adjustment is obtained according to the virtual object, the key point information of the target object, and the key point information of the standard object.
The target magnification is a parameter for adjusting the size and position of the virtual object on the target object.
In step S25, the position and size of the virtual object on the target object are adjusted according to the target magnification and the zoom information.
The virtual object self-adaptive adjusting method comprises the steps of identifying a video frame containing a target object to obtain key point information, zooming information and contour information of the target object, generating a virtual object according to the contour information, obtaining key point information of a standard object corresponding to the target object, obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object, and adjusting the position and the size of the virtual object on the target object according to the target multiplying power and the zooming information. By the method, the position and the size of the virtual object on the target object can be adjusted according to the target magnification and the zooming information, so that the virtual object is attached to the real image.
Referring to fig. 3, which is a schematic flowchart of the refining step of step S24, step S24 obtains a target magnification for adaptive adjustment according to the virtual object, the key point information of the target object, and the key point information of the standard object, and specifically includes:
in step S241, a first keypoint closest to the virtual object is acquired from the keypoint information of the target object.
In the embodiment of the present disclosure, it is assumed that the target object is a human face and the virtual object is a left ear earring. The key point information of the target object may include key points such as eyes, eyebrows, nose, mouth, cheek, central face point, and the like. The first keypoint (cheek keypoint) closest to the earring of the left ear is acquired.
In step S242, a second keypoint corresponding to the first keypoint is acquired from the keypoint information of the standard object.
In the embodiment of the present disclosure, if the first key point acquired in step S241 is a cheek key point, in the key point information of the standard object, a key point corresponding to the first key point (cheek key point) is also a cheek key point, and the cheek key point in the key point information of the standard object is referred to as a second key point.
In step S243, the target magnification is obtained according to the first key point, the first central point in the key point information of the target object, the second key point, and the second central point in the key point information of the standard object.
In the embodiment of the present disclosure, the first center point is a point located at a center position of the target object, and the second center point is a point located at a center position of the standard object.
The method for adaptively adjusting the virtual object comprises the steps of identifying a video frame containing a target object to obtain key point information, zooming information and contour information of the target object, generating the virtual object according to the contour information, obtaining the key point information of a standard object corresponding to the target object, obtaining a first key point closest to the virtual object from the key point information of the target object, obtaining a second key point corresponding to the first key point from the key point information of the standard object, obtaining a target magnification according to the first key point, a first central point in the key point information of the target object, the second key point and a second central point in the key point information of the standard object, and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information. By the method, the position and the size of the virtual object on the target object can be adjusted according to the target magnification and the zooming information, so that the virtual object is attached to the real image.
Referring to fig. 4, which is a schematic flow chart of the step of refining in step S243, the obtaining the target magnification ratio according to the first key point, the first central point in the key point information of the target object, the second key point, and the second central point in the key point information of the standard object specifically includes:
in step S2431, a first distance between the first keypoint and the first center point is calculated.
In step S2432, a second distance between the second keypoint and the second center point is calculated.
In the embodiment of the present disclosure, calculating the distance between two points belongs to the prior art, and is not described herein again.
In step S2433, the target magnification is obtained according to the first distance and the second distance.
In the embodiment of the present disclosure, the ratio of the first distance d1 to the second distance d2 is taken as the target magnification s.
Fig. 5 is a flowchart illustrating a virtual object adaptive adjustment method according to an exemplary embodiment, and as shown in fig. 5, a virtual object adaptive adjustment method is used in fig. 1, and includes the following steps:
in step S51, the video frame including the target object is identified, and the key point information, the zoom information, and the contour information of the target object are obtained.
In step S52, a virtual object is generated from the contour information.
In step S53, the key point information of the standard object corresponding to the target object is acquired.
In step S54, a target magnification for adaptive adjustment is obtained according to the virtual object, the key point information of the target object, and the key point information of the standard object.
The contents described in steps S51 to S54 in the embodiment of the present disclosure are the same as those described in steps S21 to S24 in the above embodiment, and are not described in detail here.
In step S55, the third distance between the virtual object and the first center point in the key point information of the target object is enlarged by the target magnification.
In step S56, the size of the virtual object is scaled to the target magnification of the scaling information.
In the embodiment of the present disclosure, it is assumed that the target object is a human face, the virtual object is a left ear-ear ring, the first key point is a cheek key point, and the scaling information is a magnification s0, a first distance d1 between the first key point and the first center point and a second distance d2 between the second key point and the second center point are obtained, and the target magnification s is d1/d 2. A third distance d3 between the virtual object (left ear ring) and the first center point is calculated, the third distance d3 is expanded by a factor of s, and the size of the virtual object is scaled to s times s 0.
The virtual object self-adaptive adjusting method includes the steps of identifying a video frame containing a target object to obtain key point information, zooming information and outline information of the target object, generating a virtual object according to the outline information, obtaining key point information of a standard object corresponding to the target object, obtaining target magnification for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object, expanding the target magnification and zooming the size of the virtual object to the target magnification of the zooming information. By the method, the position and the size of the virtual object on the target object can be adjusted according to the target magnification and the zooming information, so that the virtual object is attached to the real image.
In an exemplary embodiment, the identifying a video frame containing a target object further includes:
and according to a time domain smoothing algorithm, smoothing the video frame.
In the embodiment of the present disclosure, for a scene such as a video, where consecutive frame images need to be processed, smoothing (such as moving average filtering) may be performed on the video frame, so as to improve jitter. And then, identifying the video frame containing the target object, thereby more accurately obtaining key point information, scaling information, contour information and the like and more accurately performing self-adaptive adjustment on the virtual object.
Fig. 6 is a block diagram illustrating a virtual object adaptive adjustment apparatus according to an exemplary embodiment. Referring to fig. 6, the virtual object adaptive adjusting apparatus includes an identification module 61, a generation module 62, a key point acquisition module 63, a magnification acquisition module 64, and an adjusting module 65, where:
the identification module 61 is configured to identify a video frame including a target object to obtain key point information, scaling information, and contour information of the target object;
a generating module 62, configured to generate a virtual object according to the contour information;
a key point obtaining module 63, configured to obtain key point information of a standard object corresponding to the target object;
a magnification acquisition module 64, configured to obtain a target magnification for adaptive adjustment according to the virtual object, the key point information of the target object, and the key point information of the standard object;
and an adjusting module 65, configured to adjust a position and a size of the virtual object on the target object according to the target magnification and the zoom information.
In an exemplary embodiment, the magnification acquisition module 64 is configured to perform acquiring a first keypoint closest to the virtual object from the keypoint information of the target object; acquiring a second key point corresponding to the first key point from the key point information of the standard object; and obtaining the target magnification according to the first key point, a first central point in the key point information of the target object, the second key point and a second central point in the key point information of the standard object.
In an exemplary embodiment, the magnification acquisition module 64 is configured to perform calculating a first distance between the first keypoint and the first center point; calculating a second distance between the second keypoint and the second center point; and obtaining the target magnification according to the first distance and the second distance.
In an exemplary embodiment, the magnification acquisition module 64 is configured to perform a ratio of the first distance to the second distance as the target magnification.
In an exemplary embodiment, the adjusting module 65 is configured to perform expanding the target magnification by a third distance between the virtual object and the first central point in the key point information of the target object; and scaling the size of the virtual object to be the target magnification of the scaling information.
In an exemplary embodiment, the virtual object adaptive adjusting apparatus further includes a smoothing module configured to perform smoothing on the video frame according to a temporal smoothing algorithm.
For specific limitations of the virtual object adaptive adjustment device, reference may be made to the above limitations of the virtual object adaptive adjustment method, which is not described herein again. The modules in the virtual object adaptive adjusting device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a virtual object adaptive adjustment method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
identifying a video frame containing a target object to obtain key point information, zooming information and outline information of the target object;
generating a virtual object according to the contour information;
acquiring key point information of a standard object corresponding to the target object;
obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a first key point closest to the virtual object from the key point information of the target object;
acquiring a second key point corresponding to the first key point from the key point information of the standard object;
and obtaining the target magnification according to the first key point, a first central point in the key point information of the target object, the second key point and a second central point in the key point information of the standard object.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating a first distance between the first keypoint and the first central point;
calculating a second distance between the second keypoint and the second center point;
and obtaining the target magnification according to the first distance and the second distance.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and taking the ratio of the first distance to the second distance as the target magnification.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
expanding the target magnification by a third distance between the virtual object and a first central point in the key point information of the target object;
and scaling the size of the virtual object to be the target magnification of the scaling information.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and according to a time domain smoothing algorithm, smoothing the video frame.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
identifying a video frame containing a target object to obtain key point information, zooming information and outline information of the target object;
generating a virtual object according to the contour information;
acquiring key point information of a standard object corresponding to the target object;
obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a first key point closest to the virtual object from the key point information of the target object;
acquiring a second key point corresponding to the first key point from the key point information of the standard object;
and obtaining the target magnification according to the first key point, a first central point in the key point information of the target object, the second key point and a second central point in the key point information of the standard object.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating a first distance between the first keypoint and the first central point;
calculating a second distance between the second keypoint and the second center point;
and obtaining the target magnification according to the first distance and the second distance.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and taking the ratio of the first distance to the second distance as the target magnification.
In one embodiment, the computer program when executed by the processor further performs the steps of:
expanding the target magnification by a third distance between the virtual object and a first central point in the key point information of the target object;
and scaling the size of the virtual object to be the target magnification of the scaling information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and according to a time domain smoothing algorithm, smoothing the video frame.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for adaptively adjusting a virtual object, the method comprising:
identifying a video frame containing a target object to obtain key point information, zooming information and outline information of the target object;
generating a virtual object according to the contour information;
acquiring key point information of a standard object corresponding to the target object;
obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
2. The method according to claim 1, wherein obtaining a target magnification for adaptive adjustment according to the virtual object, the key point information of the target object, and the key point information of the standard object comprises:
acquiring a first key point closest to the virtual object from the key point information of the target object;
acquiring a second key point corresponding to the first key point from the key point information of the standard object;
and obtaining the target magnification according to the first key point, a first central point in the key point information of the target object, the second key point and a second central point in the key point information of the standard object.
3. The method according to claim 2, wherein obtaining the target magnification according to the first keypoint, a first central point in the keypoint information of the target object, the second keypoint, and a second central point in the keypoint information of the standard object comprises:
calculating a first distance between the first keypoint and the first central point;
calculating a second distance between the second keypoint and the second center point;
and obtaining the target magnification according to the first distance and the second distance.
4. The method of claim 3, wherein obtaining the target magnification according to the first distance and the second distance comprises:
and taking the ratio of the first distance to the second distance as the target magnification.
5. The method according to any one of claims 1 to 4, wherein the adjusting the position and size of the virtual object on the target object according to the target magnification and the zoom information comprises:
expanding the target magnification by a third distance between the virtual object and a first central point in the key point information of the target object;
and scaling the size of the virtual object to be the target magnification of the scaling information.
6. The method of any one of claims 1 to 4, wherein the identifying a video frame containing a target object further comprises:
and according to a time domain smoothing algorithm, smoothing the video frame.
7. An apparatus for adaptive adjustment of virtual objects, the apparatus comprising:
the identification module is used for identifying the video frame containing the target object to obtain key point information, zooming information and outline information of the target object;
the generating module is used for generating a virtual object according to the contour information;
the key point acquisition module is used for acquiring key point information of a standard object corresponding to the target object;
the multiplying power acquisition module is used for obtaining target multiplying power for self-adaptive adjustment according to the virtual object, the key point information of the target object and the key point information of the standard object;
and the adjusting module is used for adjusting the position and the size of the virtual object on the target object according to the target magnification and the zooming information.
8. The apparatus of claim 7, wherein the adjustment module is specifically configured to:
expanding the target magnification by a third distance between the virtual object and a first central point in the key point information of the target object;
and scaling the size of the virtual object to be the target magnification of the scaling information.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 6 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111462337A (en) * | 2020-03-27 | 2020-07-28 | 咪咕文化科技有限公司 | Image processing method, device and computer readable storage medium |
| CN111640196A (en) * | 2020-06-08 | 2020-09-08 | 浙江商汤科技开发有限公司 | Space capsule special effect generation method and device, electronic equipment and storage medium |
| CN115048001A (en) * | 2022-06-16 | 2022-09-13 | 亮风台（云南）人工智能有限公司 | Virtual object display method and device, electronic equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103631370A (en) * | 2012-08-28 | 2014-03-12 | 腾讯科技（深圳）有限公司 | Method and device for controlling virtual image |
| US9129404B1 (en) * | 2012-09-13 | 2015-09-08 | Amazon Technologies, Inc. | Measuring physical objects and presenting virtual articles |
| CN109063539A (en) * | 2018-06-08 | 2018-12-21 | 平安科技（深圳）有限公司 | The virtual usual method of glasses, device, computer equipment and storage medium |
| US20190221041A1 (en) * | 2018-01-12 | 2019-07-18 | Beijing Xiaomi Mobile Software Co., Ltd. | Method and apparatus for synthesizing virtual and real objects |
| CN110058685A (en) * | 2019-03-20 | 2019-07-26 | 北京字节跳动网络技术有限公司 | Display methods, device, electronic equipment and the computer readable storage medium of virtual objects |
| CN110069125A (en) * | 2018-09-21 | 2019-07-30 | 北京微播视界科技有限公司 | The control method and device of virtual objects |
| CN110070481A (en) * | 2019-03-13 | 2019-07-30 | 北京达佳互联信息技术有限公司 | Image generating method, device, terminal and the storage medium of virtual objects for face |
| CN110069126A (en) * | 2018-11-16 | 2019-07-30 | 北京微播视界科技有限公司 | The control method and device of virtual objects |
-
2019
- 2019-11-29 CN CN201911201523.1A patent/CN110910512B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103631370A (en) * | 2012-08-28 | 2014-03-12 | 腾讯科技（深圳）有限公司 | Method and device for controlling virtual image |
| US9129404B1 (en) * | 2012-09-13 | 2015-09-08 | Amazon Technologies, Inc. | Measuring physical objects and presenting virtual articles |
| US20190221041A1 (en) * | 2018-01-12 | 2019-07-18 | Beijing Xiaomi Mobile Software Co., Ltd. | Method and apparatus for synthesizing virtual and real objects |
| CN109063539A (en) * | 2018-06-08 | 2018-12-21 | 平安科技（深圳）有限公司 | The virtual usual method of glasses, device, computer equipment and storage medium |
| CN110069125A (en) * | 2018-09-21 | 2019-07-30 | 北京微播视界科技有限公司 | The control method and device of virtual objects |
| CN110069126A (en) * | 2018-11-16 | 2019-07-30 | 北京微播视界科技有限公司 | The control method and device of virtual objects |
| CN110070481A (en) * | 2019-03-13 | 2019-07-30 | 北京达佳互联信息技术有限公司 | Image generating method, device, terminal and the storage medium of virtual objects for face |
| CN110058685A (en) * | 2019-03-20 | 2019-07-26 | 北京字节跳动网络技术有限公司 | Display methods, device, electronic equipment and the computer readable storage medium of virtual objects |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111462337A (en) * | 2020-03-27 | 2020-07-28 | 咪咕文化科技有限公司 | Image processing method, device and computer readable storage medium |
| CN111462337B (en) * | 2020-03-27 | 2023-08-18 | 咪咕文化科技有限公司 | Image processing method, device and computer readable storage medium |
| CN111640196A (en) * | 2020-06-08 | 2020-09-08 | 浙江商汤科技开发有限公司 | Space capsule special effect generation method and device, electronic equipment and storage medium |
| CN115048001A (en) * | 2022-06-16 | 2022-09-13 | 亮风台（云南）人工智能有限公司 | Virtual object display method and device, electronic equipment and storage medium |
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|---|---|
| CN110910512B (en) | 2024-04-30 |
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