Target detection method

Abstract

The invention provides a target detection method. The method comprises the following steps: extracting image features to generate a feature map; performing up-sampling on the feature map to obtain an amplified feature map; connecting the amplified feature map to a category prediction head, a width and height prediction head and a central point offset prediction head; adding a category attention network into the category prediction head, and mining effective information between targets which are far away from each other within the category and between the categories but are semantically related; supervising training of each prediction head through supervising information generated by encoding a real target frame; and frame-selecting an identification object in the image to be detected according to a result output by each prediction head, and marking a classification result. According to the method, category attention for further judgment of target categories and scale adaptive coding for frame regression are combined, so that the network can associate intra-class and inter-class features, and effective information between intra-class and inter-class targets which are far away from each other and are semantically related is mined, meanwhile, more accurate frame selection can be carried out according to the scale change of the detection target, so that the detection accuracy and the frame selection precision are improved.

Description

technical field [0001] The invention belongs to the field of computer vision target detection, and in particular relates to a target detection method. Background technique [0002] Object detection is a common problem in the field of machine vision. It is an image segmentation based on the detection of geometric and statistical features of the target. It combines target segmentation and recognition in order to obtain accurate target detection results. Target detection is to combine target positioning and target classification, and use multi-directional knowledge such as image processing technology and machine learning to locate objects of interest from images or videos. The target classification part is responsible for judging whether the input image contains classified objects, and the target positioning part is responsible for indicating the position of the target object, and marking the position with a bounding rectangle. Object detection plays an important role in many...

AI Technical Summary

Problems solved by technology

[0006] In view of the above defects or improvement needs of the prior art, the present invention proposes a target detection method to solve the limitations of current target detection based on regression problems

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