Fixed-lens real-time monitoring video feature extraction method based on SIFT feature clustering
A technology of real-time monitoring and video features, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as feature extraction that are not suitable for monitoring video
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Embodiment 1
[0064] The embodiment of the present invention provides a real-time video feature extraction method for the surveillance video which is in the same shot for a long time and basically does not have the feature of shot switching, hereinafter referred to as the method.
[0065] In this method, SIFT feature technology is needed, which is a basic technology used in this method. Its role in this method is to extract feature points from each video frame.
[0066] The following is a brief introduction to SIFT.
[0067] SIFT, or Scale-invariant feature transform (SIFT) for short, is a local image feature extraction algorithm proposed by Professor David G. Lowe in 1999 and further improved in 2004. The SIFT feature is a local feature of an image. Its feature points have good stability and are not affected by image rotation, scaling, and affine. It has a high anti-interference ability for external interference factors such as light and viewing angle changes.
[0068] At the same time, ...
Embodiment 2
[0133] In this embodiment, the description of the specific implementation and effect of this method is carried out with the processing of a video segment SL05_540P.
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