A video concentration method and device
A video concentration and video technology, applied in the field of video processing, can solve the problem of insufficient concentration precision of concentrated video
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no. 1 example
[0087] see figure 1 , which is a schematic flow chart of a video concentration method provided in this embodiment, the method includes the following steps:
[0088] S101: Acquire a video to be concentrated, where the video to be concentrated includes multiple moving objects.
[0089] In this embodiment, the original video that needs to be condensed is defined as the video to be condensed, such as surveillance video in some scenarios. The video to be concentrated is any video that may contain any moving objects, such as moving objects such as people and cars. Here, each moving object in the video to be concentrated is defined as a moving target.
[0090] In this embodiment, the background image in the video to be concentrated can be extracted through background modeling. Wherein, the background image refers to a clean background image after removing moving objects in the video to be concentrated, and the background image is obtained by continuously updating the background ima...
no. 2 example
[0151] It should be noted that this embodiment will introduce specific implementation manners of step S201 and step S202 in the first embodiment.
[0152] In this example, see image 3 In the schematic diagram of the clustering-based grouping process shown in the first embodiment, the step S201 of "obtaining each initial group by grouping overlapping moving objects in the video to be concentrated" may include the following steps S301-S302:
[0153] S301: Extract the clustering features corresponding to each moving target from the video to be concentrated.
[0154] In this embodiment, all overlapping moving objects in the video to be concentrated can be grouped by a clustering algorithm, so as to obtain each initial group, and each initial group includes one or more moving objects. In order to obtain each initial grouping through the clustering algorithm, it is necessary to extract the clustering features corresponding to each moving object from the video to be concentrated, t...
no. 3 example
[0187]This embodiment will introduce a video concentrating device, and for related content, please refer to the foregoing method embodiments.
[0188] see Figure 6 , which is a schematic composition diagram of a video concentrating device provided in this embodiment, the device 600 includes:
[0189] The video to be condensed acquiring unit 601 is configured to acquire the video to be condensed, the video to be condensed includes a plurality of moving objects;
[0190] The target combination selection unit 602 is configured to select a moving target combination mode for each condensed image, and each condensed image is each frame image obtained after condensing the video to be condensed;
[0191] The video condensing processing unit 603 is configured to perform video condensing on the video to be condensed according to the combination manner of the moving objects in each condensed image.
[0192] In an implementation of this embodiment, the target combination selection unit...
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