Capstone Project

Back to listing
Group 2008-12 Status completed
Title Hardware (FPGA) based moving object detection for automated video surveillance
Supervisor Dr. A. Amer
Description Automated video surveillance provides ubiquitous vigilance of complex and dangerous environments. Real-time detection of moving objects in video sequences is a fundamental step in automated video surveillance and many other vision systems. Moving object detection requires subtracting each subsequent video image from a reference video image, called background frame. A background frame needs to be estimated adaptively considering various factors such as illumination changes, camera movement, and shadowing effects.

The objective of this project is to design and implement an efficient FPGA-based architecture for a moving object detection algorithm. Students will be given to study a state-of-the-art adaptive moving object detection algorithm, and explore it for the hardware parallelism. The students will be guided to understand main video-processing concepts of the algorithm to implement in hardware. The algorithm will be then modeled in MATLAB before coding it in VHDL. The architecture will efficiently utilize FPGA's inherent resources in order to maximize speed and minimize the area and power. Individual modules (components) will be verified with test benches, and then the overall functionality of the algorithm will be demonstrated with a top-level test bench.

In this project, students will have access to some VHDL simulation models such as DDR memory controllers, video acquisition and storage modules, and register interfaces.
Student Requirement Students should have good knowledge in digital circuit design in VHDL. Fundamentals of FPGAs and signal processing are required. Students will be introduced to fundamentals of video processing required in the project.
Tools VHDL Simulator (Aldec, Modelsim, e.t.c.), MATLAB, and Xilinx ISE Foundation. An introduction to advanced tools will be given.
Number of Students 3-5
Students
Comments:
Links: http://users.encs.concordia.ca/~amer/teach/elec490/