Multi-target Detection Method Based on Multi-scale CLG Optical Flow Method

Abstract

Abstract: Multi-target detection is an important research direction in computer vision. How to accurately detect targets in military, life, industry and other aspects have very important research significance. Aiming at the poor robustness to noise of traditional optical flow methods in target detection, in order to improve the robustness of the algorithm against noise, the CLG optical flow method is combined with the idea of multi-scale. The main idea of multi-scale is to build an image pyramid, calculate the optical flow vector from coarse to fine, and change the square of L2 norm to L1 norm. Experimental results show that the improved multi-scale CLG optical flow algorithm has better overall performance than the original CLG optical flow algorithm, indicating that the multi-scale CLG optical flow algorithm has better robustness to noise, and can better estimate the optical flow of images.

Key words: multi-object detection, CLG optical flow method, L1 norm, multi-scale, image pyramid

REN Chao-yu, ZHAO Dong-e, ZHANG Bin, YANG Xue-feng, CHU Wen-bo. Multi-target Detection Method Based on Multi-scale CLG Optical Flow Method[J]. Computer and Modernization, 2022, 0(04): 33-37.

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