Abstract
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.
Highlights
Smart video surveillance is a process of automatically identifying in video sequences, objects, behaviors or events preset by a user or learned by the system
The parallelization is the method used for creatinga hardware architecture that meets this requirement
The implementation of the proposed architecture has been done on a Xilinx Virtex 5 XC5VLX200TFPGA device. it is necessary to represent both the integer and fractional portion of a number
Summary
Smart video surveillance is a process of automatically identifying in video sequences, objects, behaviors or events preset by a user or learned by the system. In this study an embedded architecture for moving object tracking using Kalman filter, is proposed. The Kalman filter is based on a diagram of the type prediction-correction.
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