Abstract
The design of smart video surveillance systems is an active research field among the computer vision community because of their ability to perform automatic scene analysis by selecting and tracking the objects of interest. In this paper, we present the design and implementation of an FPGA-based standalone working prototype system for real-time tracking of an object of interest in live video streams for such systems. In addition to real-time tracking of the object of interest, the implemented system is also capable of providing purposive automatic camera movement (pan-tilt) in the direction determined by movement of the tracked object. The complete system, including camera interface, DDR2 external memory interface controller, designed object tracking VLSI architecture, camera movement controller and display interface, has been implemented on the Xilinx ML510 (Virtex-5 FX130T) FPGA Board. Our proposed, designed and implemented system robustly tracks the target object present in the scene in real time for standard PAL (720 × 576) resolution color video and automatically controls camera movement in the direction determined by the movement of the tracked object.
Highlights
One of the most significant tasks of smart video surveillance system, is usually performed in the context of higher-level visual surveillance applications that require the location of the object in every frame [1]
For a robust and real-time testing of our implementation, the implemented system has been run for different real-world scenarios for tracking of an object of interest in live color video streams directly coming from the camera
We have proposed and described the design and implementation of a standalone system for object tracking in real time, with automatic camera pan-tilt capabilities
Summary
One of the most significant tasks of smart video surveillance system, is usually performed in the context of higher-level visual surveillance applications that require the location of the object in every frame [1]. Development of a real-time object tracking system is a very challenging task due to issues arising from the motion of the camera, complex object motion, the complex background of the scene (the presence of other moving objects) and real-time processing requirements. These challenges may cause tracking degradation and even failures. In order to deal with these different challenges, researchers have used numerous approaches for object tracking These algorithms usually focus on different problems in visual object tracking and, have different properties and characteristics, resulting in different responses and performances for the same input video sequences.
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