Title :
The combination of CSLBP and LBP feature for pedestrian detection
Author :
Jingjing Li ; Yong Zhao ; Dongbing Quan
Author_Institution :
Sch. of Electron. & Comput. Eng., Peking Univ., Shenzhen, China
Abstract :
Local Binary Pattern (LBP) feature has attracted increasing interest in pedestrian detection tasks, but it requires high dimensionality to gain promising performance. To address this problem, we make three main contributions. First, Center-Symmetric Local Binary Patterns (CSLBP) feature is introduced to pedestrian detection. It´s the first time to extract CSLBP operator in an approach similar to basic LBP operator. Second, we propose the operator combining CSLBP1,8 pattern and uniform LBP1,8 pattern, named combined-LBP descriptor for convenience. Third, the combined-LBP operator is applied to various color spaces. Experiments on INRIA pedestrian database show that combined-LBP operator based pedestrian detector achieve state of art performance with miss rate of 6.04% at FPPW=10-4 in gray-scale image, and the proposed operator in oRGB color space obtain superior result with miss rate of 2.75% at FPPW=10-4.
Keywords :
feature extraction; image colour analysis; object detection; pedestrians; traffic engineering computing; CSLBP feature; FPPW; INRIA pedestrian database; LBP feature; center-symmetric local binary patterns feature; color spaces; combined-LBP descriptor; gray-scale image; high dimensionality; local binary pattern feature; oRGB color space; pedestrian detection tasks; Databases; Detectors; Feature extraction; Gray-scale; Histograms; Image color analysis; Pattern recognition; Center-Symmetric Local Bbinary Patterns (CSLBP); Local Binary Patterns (LBP); pedestrian detection;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
DOI :
10.1109/ICCSNT.2013.6967172