Field Programmable Gate Array Implementation of Parts-Based Object Detection for Real Time Video Applications
Deborah Goshorn, Junguk Cho, Ryan Kastner, Shahnam Mirzaei · 2010
The emergence of smart cameras has been fueled by increasingly advanced computing platforms that are capable of performing a variety of real-time computer vision algorithms. Smart cameras provide the ability to understand their environment. Object detection and behavior classification play an important role in making such observations. This paper presents a high-performance FPGA implementation of a generalized parts-based object detection and classifier that runs with capability of 266 frames/sec. The detection algorithm is easily reconfigured by simply loading a new representation into on-board memory, i.e., the FPGA can detect and classify a newly specified object and behavior without any changes to the hardware implementation.