Adaptive multitarget detection algorithm based on feature extraction

We propose a target detection algorithm that combines confidence and feature extraction to address the problems of existing target detection algorithms, such as low detection accuracy and susceptibility to occlusion. Based on the traditional algorithm, this algorithm introduces the adaptive strategy objective according to the motion complexity of the video block, combined with the target contour field retrieval to enhance the precision of the algorithm. Experimental results show that in different environments, the algorithm in this paper has better detection accuracy and anti-obscuration ability than other existing algorithms. And it still maintains a high resolution for multi-targets, which effectively reduces the problems of target loss, identity jumping, and so on.