Abstract:Target recognition is the basic purpose of computer vision, it is also one of the key components in the field of artificial intelligence.With the advent of the information age, the popularity of video capture tools, massive video data to human identification has brought great challenges. At this stage, video recognition technology has been widely used in simple scenes such as intelligent transportation field and production quality inspection field. How to realize the target recognition and detection from complex scenes has become a more important and difficult issue. In response to this problem, this paper presents a moving target recognition algorithm in complex scenes. First, an improved optical flow algorithm is proposed to mark the moving target region quickly by time series and spatial pixel changes; Secondly, the sliding window of the target area is detected to match the model of each part of the human body, and the feedback information is modeled by a tree structure. Through experiments, this method can detect faster than detection algorithm based on depth learning while ensuring high accuracy, and can meet the requirements of real-time monitoring.