Research On Tracking Algorithm For Visual Target Under Complex Environments

Visual target tracking is a key problem in computer vision, it has a wide range of applications in military guidance, visual surveillance, visual navigation of robots, human-computer interaction, and medical diagnose, etc. The goal of visual target tracking is to imitate the motion sensibility of human vision, empower the machine with the ability of perceiving the target motion in the image sequence, and provide an important data source for visual analysis and understanding. Visual target tracking often becomes very difficult due to complex image backgrounds and the target motion. Although visual target tracking has been widely researched and many effective algorithms have been proposed, there are still a lot of difficulties in tracking the targets in complex environments.In this dissertation, the research is focused on the tracking problems of single target and multiple targets. For single-target tracking, the work is focused on the design of the observation model. For multi-target tracking, the work is focused on the problems of the appearance and disappearance of targets in scene, the similar appearance of targets, the cross movement of targets, and occlusion, etc.The main contributions of this dissertation are summarized as follows:1. For the visual target in complex environments, a tracking algorithm based on the multi-cue adaptive fusion has been proposed. In this method, the target observation is represented by multiple cues. When fusing each cue, a fusion scheme based on fuzzy logic has been developed. The fuzzy logic adaptively adjusts the weight of each cue according to the current tracking situations, so each cue is adaptively fused during tracking, which increases the reliability of observation and improves the robustness of observation model. When tracking targets, the probabilistic particle filter has been adopted, and the...