Hardware acceleration for real-time vehicle object detection based on MPSoC *

Geng Linwen; Ding Hongchagn

doi:10.1117/12.3007348

10 October 2023 Hardware acceleration for real-time vehicle object detection based on MPSoC *

Geng Linwen, Ding Hongchagn

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279943 (2023) https://doi.org/10.1117/12.3007348
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Facing the growing demand for autonomous driving, the accuracy of vehicle target detection has become a crucial issue. Given the challenges of mainstream target detection algorithms on image processors, such as large model parameters, poor real-time performance, high power consumption, and high cost, this paper proposes a real-time vehicle target detection scheme based on MPSoC. By replacing CSPdarknet53 in YOLOV4 with MobilenetV3, lighter feature extraction is achieved. PANET structure is used for feature fusion, and depthwise separable convolution is incorporated. Channel Attention (CA) module is adopted to enhance detection accuracy. Ultimately, the model's floating-point parameters are quantized to 16-bit fixed-point numbers and deployed on the MPSoC. Experimental results on the Kitti vehicle dataset demonstrate that the proposed scheme achieves an precision of 81.97, an FPS of 47.23, and power consumption of 10W, increasing the detection speed by 359.6% compared to CPU and reducing power by 91.4% compared to GPU. The proposed scheme can satisfy the requirements of real-time target detection and can be deployed on power-limited devices such as intelligent vehicles

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Geng Linwen and Ding Hongchagn "Hardware acceleration for real-time vehicle object detection based on MPSoC *", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279943 (10 October 2023); https://doi.org/10.1117/12.3007348

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KEYWORDS

Object detection

Detection and tracking algorithms

Target detection

Artificial intelligence

Autonomous vehicles

Convolution

Power consumption

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