Method for pedestrian weight recognition in video surveillance scene
A pedestrian re-identification and video surveillance technology, applied in the field of pedestrian re-identification, to achieve the effect of simple attribute classification and high accuracy
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[0050] As shown in the attached picture, figure 1 The overall process of applying the method of this paper for pedestrian re-identification. Among them, the key steps involved in the present invention are training the CNN network and optimizing attribute weights, calculating attribute features, etc. The calculation and sequential output of the distance matrix are common steps for pedestrian re-identification applications.
[0051] figure 2 For this paper, the convolutional network used to extract deep features and obtain semantic attribute features is called FT-FNN (Fine-Tuning Feature Fusion Net). The upper part of the figure is the Alex network, and the lower part is a manually extracted feature ELF16, and the two are fused in the seventh fully connected layer. The number of nodes in the output layer of the network layer is consistent with the number of attributes to be identified.
[0052] as attached figure 1 As shown in, a method for pedestrian re-identification in a...
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