A Pedestrian Re-Identification Method Based on Label Uncertainty and Body Component Model
A pedestrian re-identification and uncertainty technology, applied in the field of computer vision, can solve the problems of large differences, incomplete and accurate classification confidence of local information, etc., and achieve the effect of improving performance and wide application value.
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[0036] like figure 1 Shown is a flow chart of a pedestrian re-identification method based on label uncertainty and human body component model. The specific steps include:
[0037] (1) Construct a deep neural network model based on human body components;
[0038] In the step (1), the ResNet-50 network is used as the basic structure to modify and adjust.
[0039] In this embodiment, a deep neural network model for six classification tasks based on human body components is constructed.
[0040] The construction method of the deep neural network is as follows: remove the fully connected layer whose output dimension is 1000 in the ResNet-50 network, modify the downsampling rate stride=2 in layer4 to stride=1; divide it into 6 after the pooling layer Each part contains a fully connected layer of 256 neurons, a batch normalization layer and a dropout layer, and finally a classification fully connected layer.
[0041] (2) initialize the deep neural network model of construction, an...
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