Embedded Architecture for Object Tracking using Kalman Filter

Intelligent video is a new area of research fairly wide allowing to do a study, analysis, or interpretation of digital video such as motion analysis. However, for a video surveillance system, a motion analysis task of digital video includes the detection of moving objects and their tracking. The object detection allows the location of the regions of interest, which represents a change of movement. The purpose of tracking is to maintain the identity of objects detected over time by the estimation or the location of their position in each frame of the sequence. The most popular tracking algorithm is the Kalman filtering. In this study a hardware architecture for moving object tracking using Kalman filter on a FPGA board, is proposed.