Target detection method and system based on dynamic memory and motion perception

Abstract

The invention belongs to the technical field of computer vision, and specifically relates to a method and device for object detection based on dynamic memory and motion perception, aiming to solve the problem of low object detection accuracy caused by video false detection. The method includes: using the neural network to obtain the feature map corresponding to the current frame image in the target video, and obtaining the target candidate frame; according to the feature map with the largest resolution and the dynamic memory feature map corresponding to the previous frame image, obtaining the corresponding frame image. Dynamic memory feature map; according to the dynamic memory feature map corresponding to the current frame image and the feature map with the largest resolution, the motion feature map of the current frame is obtained; the feature map with the largest resolution and the motion feature map of the current frame image are fused together to obtain Fusion feature map; obtain the fusion feature of each target candidate frame according to the fusion feature map; use the fusion feature for target detection. Based on the above method, more robust and stable target detection results can be obtained.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a target detection method and system based on dynamic memory and motion perception. Background technique [0002] The task of object detection is to find out the objects of interest in the image or video, and detect their position and size at the same time, which is one of the core problems in the field of computer vision. With the application and development of convolutional neural networks, object detection based on single-frame images has made great progress, but object detection based on video still has certain characteristic difficulties, such as motion blur and video defocus. [0003] At present, there are mainly two ways to suppress video false detection in video object detection. The first method is to use the detector to detect each frame of the video separately, and then use the heuristic algorithm to post-process the detection results of each frame...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above problems in the prior art, that is, to solve the problem of low target detection accuracy caused by video false detection, one aspect of the present invention provides a target detection method based on dynamic memory and motion perception, include:

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