Target tracking method based on multi-feature self-adaption fusion and on-line study
A target tracking and self-adaptive technology, applied in the field of target tracking, can solve the problem that the target tracking method cannot adapt to the change of the target shape, and achieve the effect of enhancing adaptability, improving accuracy and robustness, and overcoming singleness
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2013-07-10
- Estimated Expiration
- Not applicable · inactive patent
Smart Images
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Abstract
Description
technical field
[0001] The invention relates to the field of target tracking, in particular to a target tracking method based on multi-feature adaptive fusion and online learning. Background technique
[0002] Video object tracking refers to the process of object detection, representation and trajectory extraction in video sequences. Video object tracking has practical application requirements in video surveillance, event analysis, human-computer interaction and other fields.
[0003] At present, the world's most advanced surveillance systems cannot perfectly handle dynamic tracking tasks in complex scenes, such as: deformation, occlusion, lighting changes, shadows or tracking in crowded environments. Object tracking remains a challenge, especially when objects are partially occluded and deformed.
[0004] Single-feature-based tracking methods usually initialize the target region, extract arbitrary target features, such as: color features, and search and match them in the ...
Examples
Embodiment Construction
[0047] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0048] In order to avoid the problem of tracking drift and adapt to the change of target shape, the embodiment of the present invention provides a target tracking method based on multi-feature adaptive fusion and online learning. Online learning can overcome target deformation and The problems caused by tracking drift have better achieved the expected tracking effect, see figure 1 , see the description below:
[0049] 101: Take a frame of any video sequence as input, select a target area from a frame of image, extract target features and use them as template features;
[0050] Wherein, the operation of selecting the target area is well known to those skilled in the art, and the target area is a rectangular area, for example: according...