Hardware and Software Co-Design for Object Detection with Modified ViBe Algorithm and Particle Filtering Based Object Tracking

Abstract

This paper describes a hardware and software codesign approach for object detection and tracking algorithm which is based on modified ViBe background subtraction method and scale adaptable particle filtering algorithm. The modified ViBe performs with a close accuracy to the original work of ViBe but with less complexity and it outperforms the Mixture of Gaussian(MoG) method. Since the modified algorithm has a low off chip memory access requirement, the real time object detection in embedded level with the help of hardware acceleration techniques could be achieved. The implemented particle filtering algorithm is capable of adapting to the scale variation of the tracking objects. After careful investigation of the time consumption profile of each function in our algorithm, the complete algorithm was implemented in IoT edge devices targeted Avnet Ultra 96 development board which is based on Xilinx Zynq MPSoC. We could achieve an average frame rate of 40 fps for a $854\times 480$ resolution data set.