Spatial-temporal feature aggregation method and system combined with attention mechanism and terminal

Abstract

The invention provides a spatial-temporal feature aggregation method and system combined with an attention mechanism, and a terminal, and the method comprises the steps: extracting the spatial domainfeatures of a pedestrian in a deep network through a convolutional neural network, and obtaining the time domain features of the pedestrian through the spatial domain features comprehensively extracted through a recurrent neural network; respectively generating corresponding quality-sensitive attention scores and frame-sensitive attention scores by adopting a feature extraction network so as to dynamically fuse spatial domain and time domain features; carrying out linear superposition fusion to obtain quality-sensitive spatial domain features and frame-sensitive time domain features to obtainpedestrian space-time feature expression; carrying out network training on the upper, middle and lower parts of a pedestrian to obtain corresponding local features with complementary properties, and obtaining feature expressions with higher discrimination through splicing. The method and system have good robustness, and can better solve and adapt to the conditions of shielding, light change and the like; and by combining the spatial domain and time domain characteristics of the pedestrian, the detail characteristics of the pedestrian are mined, so that the method and system can play better performance and efficiency in the next step of pedestrian recognition.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a spatio-temporal feature aggregation method, system and terminal of a joint attention mechanism. Background technique [0002] Pedestrian re-identification is a key task in intelligent video surveillance, and it has been a research hotspot in the field of computer vision in recent years. It is suitable for security and public places and other technical fields. Pedestrian re-identification can be defined as: in a non-overlapping video surveillance network, for a given person in one camera, determine whether it appears in other cameras or not. It is an automatic target recognition technology, which can quickly locate interested human targets in the surveillance network, and is an important step in applications such as intelligent video surveillance and human behavior analysis. [0003] How to extract enough discriminative features from limited data is a key ch...

AI Technical Summary

Problems solved by technology

However, the recurrent neural network has the problem of gradient divergence, cannot well synthesize the information of the early image frames, and lacks the necessary spatial information, which limits the final recognition accuracy

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