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Mao Qi-rong
Jiangsu University

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Pedestrian Detection Based on Sparse and Low-Rank Matrix Decomposition Cheng Ke-yang; Mao Qi-rong; Zhan Yong-zhao
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

This article puts forward a novel system for pedestrian detection tasks, which proposing a model with sparse and low-rank matrix decomposition, jointly alternating direction method to solve the convex relaxation problem. We present an efficient pedestrian detection system using mixing features with sparse and low-rank matrix decomposition to combine into a Kernel classifier. Results presented on our data set show competitive accuracy and robust performance of our system outperforms current state-of-the-art work. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3859
Co-Authors Cheng Ke-yang Zhan Yong-zhao