An Energy-Efficient, Resource-Efficient and High Frame-Rate End-to-End Pedestrian Detector Using HOG-SVM for Intelligent Edge Devices

Jipeng Wang1; Jianhui Song1; Bingqiang Liu1; Zixuan Shen1; Yu Jiang2; Fengwei An3; Chao Wang1; Jiang Tang1

10.1109/IECON51785.2023.10311903

2023-10

IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

1553-572X

979-8-3503-3183-7

IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

1-6

16-19 Oct. 2023

Singapore, Singapore

This paper proposes a Histogram of Oriented Gradients-Support Vector Machine (HOG-SVM) based pedestrian detector with an end-to-end fully-pipelined architecture to achieve a high frame rate by improving the throughput, and reduce the power consumption by minimizing the data movement. To further improve the energy efficiency under the high frame rate, a bit-width pruning method is used to remove the gray-scale converter's redundant data bit width, and a block-score normalization is employed to significantly reduce the normalizer's required divisions. The reduced computation amount also saves the hardware overhead while maintaining the same calculation accuracy. Besides, a modeling and analysis method of the SVM-classifier-Multiply-ACcumulate (MAC) array is proposed to further improve the energy efficiency and save the logic resources, by optimizing the array size with a hardware utilization of 98.4% while maintaining the same throughput. The FPGA implementation results of $640\times 480$ video show a high frame rate of up to 439 fps @143 MHz and a high energy efficiency of 0.76 nJ/pixel with 46.7% fewer LUTs, 22.4% fewer registers, 88.3% fewer DSPs, compared to the state-of-the-art design. The ASIC implementation in 55 nm also confirms a high energy efficiency of 0.35 nJ/pixels at 613 fps and 200 MHz as well as a hardware overhead of 177 k gates and 108 Kbits SRAM.

Pedestrian Detection HOG-SVM Hardware Accelerator Artificial Intelligence Intelligent Robots Edge Devices

其他

EI

20235015212046

Computation Theory ; Energy Efficiency ; Intelligent Robots

Energy Conservation:525.2 ; Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Computer Software, Data HAndling And Applications:723 ; Robot Applications:731.6

IEEE

1.School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
2.School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, China
3.School of Microelectronics, Southern University of Science and Technology, Shenzhen, China

Jipeng Wang,Jianhui Song,Bingqiang Liu,et al. An Energy-Efficient, Resource-Efficient and High Frame-Rate End-to-End Pedestrian Detector Using HOG-SVM for Intelligent Edge Devices[C],2023:1-6.