A pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning
A pedestrian re-recognition and dictionary learning technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as difficulty in matching similar pedestrians, and achieve good results
Active Publication Date: 2019-03-08
KUNMING UNIV OF SCI & TECH
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Abstract
The invention relates to a pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning, belonging to the technical field of digital image recognition. At first, that original image features are mapped to a low-dimensional discrimination space to reduce the divergence between the same pedestrian unde different angles of view. In addition, in order to further enhance the discriminability of the dictionary, it is assumed that the same pedestrian enjoys the same coding coefficient in the low-dimensional space, and the stretching regularity term is added to force the pedestrians with similar visual features but different identities to have large coding coefficients. In order to fully mine label information of label samples, label consistency constraints are added, and a dictionary learning model based on the combination of dictionary and classifier is constructed. In the test phase, pedestrian recognition is carried out by similarity measurement based on the parameters learned from the dictionary learning model. The method provided by the invention has the higher recognition rate than the traditional method.
Application Domain
Character and pattern recognition
Technology Topic
Similarity measurePedestrian recognition +11
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