Target detection method, device, equipment and storage medium

Abstract

The invention discloses a target detection method, a target detection device, equipment and a storage medium. The method comprises the steps: obtaining video data, carrying out the preprocessing of afirst image sequence of the video data, obtaining a second image sequence with a background image removed, inputting the second image sequence into a trained detection model for target detection, andobtaining a target detection result. On one hand, only a foreground target is reserved for an image with a background removed, interference of other background images is avoided. A detection model pays more attention to the foreground target during learning and reasoning. Therefore, the target detection accuracy can be improved. On the other hand, since the background pixels of the input image areremoved, only the foreground pixels are seen by the detection model and are not influenced by a video or picture sequence scene at all, so that the scene migration performance of target detection isimproved.

Description

technical field [0001] The present application relates to the technical field of computer vision, and in particular to an object detection method, device, equipment and storage medium. Background technique [0002] As we all know, vision is the most direct and effective means of obtaining information. However, most monitoring systems are in the working mode of "only recording without judgment". judgment. However, there is a great waste of human resources in this way. With the emergence of computer vision intelligent video processing systems, image processing technology and machine learning methods are used to achieve video analysis such as target detection and tracking. [0003] The task of object detection is to find all the objects of interest in the image, determine their position and size. Object detection has always been the most challenging problem in the field of machine vision due to the different appearance, shape, and posture of various objects, coupled with the...

AI Technical Summary

Problems solved by technology

[0004] Existing target detection is prone to misdetection for scenes with complex backgrounds in static pictures, so the accuracy of target detection needs to be improved

In addition, the existing target detection has certain limitations in realizing the generalization performance of monitoring complex scenes. In order to improve the scene transfer performance of the target detection algorithm, a large number of data sets need to be trained, which is highly dependent on data.

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