Pedestrian detection method based on layered kernel sparse representation
A kind of kernel sparse representation, pedestrian detection technology, applied in the field of intelligent transportation, can solve the problem of not being able to adapt to the scene and the rapid change of pedestrian appearance, the classification model is difficult to distinguish pedestrians and other problems
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[0047] Such as figure 1 As shown, a pedestrian detection method based on hierarchical kernel sparse representation is to preprocess the collected traffic video to obtain the required positive and negative samples, obtain multi-scale feature vectors through hierarchical sub-block division, and construct two Dictionary-like matrix; preprocess the pedestrian images to be tested to obtain test samples, and extract pedestrian features in the same way as the dictionary construction process to form the feature vector of the test sample; use the histogram cross kernel function to process the feature vector of the test sample The kernel is sparsely decomposed, and Gaussian function weighting is used in the iterative solution process, and then the pedestrian detection is realized through the reconstruction error; specifically, the steps are as follows:
[0048] Step 1, dictionary construction:
[0049] Step 1.1, collect the traffic video from the vehicle-mounted image acquisition devic...
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