A hardware architecture for real-time object detection using depth and edge information
ACM Transactions on Embedded Computing Systems (TECS)
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Object detection is a vital task in several existing as well as emerging applications, requiring real-time processing and low energy consumption, and often with limited available hardware budget in the case of embedded and mobile devices. This paper proposes an FPGA-based object detection system that utilizes edge information to reduce the search space involved in object detection. By eliminating large amounts of search data, the proposed system achieves both performance gains, and reduced energy consumption, while requiring minimal additional hardware, making it suitable for resource-constrained FPGAs. Implementation results on an FPGA indicate performance speedups up to 4.9 times, and high energy savings ranging from 73-78%, when compared to the traditional sliding window approach for FPGA implementations.