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A Real-time Pedestrian Detection System in Street Scene Cover
By: Ai-ying Guo,  Mei-hua Xu,  Feng Ran and  Qi Wang  
Open Access
|Sep 2016

Abstract

Pedestrian detection is the key technology in Advanced Driver Assistant System (ADAS).Until recently, pedestrian detection, which is realized as the vehicle equipment, still doesn’t have the mature product. So, this thesis proposes a novel pedestrian detection system on board with the E-HOG (Histogram of Gradient) IP (intellectual property), can be used as the real time vehicle equipment. Three contributions are made in this thesis. Firstly, Sobel operator cascaded Uniform Local Binary Pattern (LBP) and E-HOG is the novel structure of pedestrian detection system. The Sobel operator gives the sliding step of Uniform LBP detection window, without using the results of LBP detection window. Through this operation, the detection speed will be improved. Second, the vehicle equipment of pedestrian detection is self-developed using FPGA as core devices. Third, E-HOG IP, which is promoted based on the HOG, can extract pedestrian or other objects feature. Without sacrifice of accuracy, this pedestrian detection on board deals with 30 fps (640x480 pixels) and can be used as the real-time detection system.

Language: English
Page range: 1592 - 1613
Submitted on: Apr 17, 2016
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Accepted on: Aug 1, 2016
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Published on: Sep 1, 2016
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2016 Ai-ying Guo, Mei-hua Xu, Feng Ran, Qi Wang, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.