Fast Pedestrian Detection for Intelligent Vehicle Based on FPGA and Monocular Vision

Xiao Dong Miao; Shun Ming Li; Min Xiang Wei; Huan Shen

doi:10.4028/www.scientific.net/AMR.651.784

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 651Fast Pedestrian Detection for Intelligent Vehicle...

Fast Pedestrian Detection for Intelligent Vehicle Based on FPGA and Monocular Vision

Abstract:

This paper presents a fast pedestrian detection algorithm for intelligent vehicle based on FPGA architecture, using AdaBoost algorithm and Haar features. We describe the hardware design including image scaling, integral image generation, pipelined processing as well as classifier, and parallel processing multiple classifiers to accelerate the computational speed of the pedestrian detection system. The proposed architecture for pedestrian detection has been tested using Verilog HDL and implemented in Xilinx Virtex-5 FPGA. Its performance has been measured about 38 times than the equivalent software implementation.

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Periodical:

Advanced Materials Research (Volume 651)

Pages:

784-788

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.651.784

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Online since:

January 2013

Authors:

Xiao Dong Miao, Shun Ming Li, Min Xiang Wei, Huan Shen

Keywords:

Field-Programmable Gate Array (FPGA), Haar Classifier, Intelligent Vehicle, Machine Vision, Pedestrian Detection, Real-Time

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