It combines genetic algorithms and truncated sequential probability ratio test to detect and track moving point targets computationally efficiently with a very low SNR.

Moving object detection and tracking in video sequences based on boundary vector field;

The technology of video based object detection and tracking is one of the hotspots in the field of computer vision, which is also the basic and important technology in the applications of smart surveillance, human-machine interface, mobile robots navigation, industrial robots hand-eye system and so on.

The thesis is focused on the study of Electro-optical Navigation based on DSP, including the design of the hardware platform and algorithm software module for moving object detection and tracking.

To implement target detection and tracking in long distance, a kind of high resolution omni-directional vision system is designed by catadioptric imaging.

This paper presents a method of moving object detecting and tracking under stationary camera, which can be used for real-time surveillance.