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http://dx.doi.org/10.5573/ieie.2014.51.10.190

Mobile Advanced Driver Assistance System using OpenCL : Pedestrian Detection  

Kim, Jong-Hee (School of Information and Communication Engineering, Inha University)
Lee, Chung-Su (School of Information and Communication Engineering, Inha University)
Kim, Hakil (School of Information and Communication Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.51, no.10, 2014 , pp. 190-196 More about this Journal
Abstract
This paper proposes a mobile-optimized pedestrian detection method using Cascade of HOG(Histograms of Oriented Gradients) for ADAS(Advanced Driver Assistance System) on smartphones. In order to use the limited resource of mobile platforms efficiently, the method is implemented by the OpenCL(Open Computing Language) library, and its processing time is reduced in the following two aspects. Firstly, the method sets a program build option specifically and adjusts work group sizes as variety of kernels in the host code. Secondly, it utilizes local memory and a LUT(Look-Up Table) in the kernel code to accelerate the program. For performance evaluation, the developed algorithm is compared with the mobile CPU-based OpenCV(Open Computer Vision) for Android function. The experimental results show that the processing speed is 25% faster than the OpenCV hogcascade.
Keywords
Pedestrian detection; OpenCL; Embedded GPGPU; ADAS; HOG;
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Times Cited By KSCI : 2  (Citation Analysis)
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