Abstract:
This paper presents a pedestrian detection approach based on Multi-block Local Binary Pattern (MB-LBP) features and Weighted Region Covariance Matrix (WRCM). Multistage c...Show MoreMetadata
Abstract:
This paper presents a pedestrian detection approach based on Multi-block Local Binary Pattern (MB-LBP) features and Weighted Region Covariance Matrix (WRCM). Multistage classifiers are used to increase the processing speed and reliability of the detection system. Using the modified 3-D B-spline Wavelet-Based Local Standard Deviation (BWLSD) techniques, the region of interest is determined. Once the pedestrian region is identified, the front end of the multistage classifier quickly determines wherever pedestrians may be present, while the back end confirms whether the first descriptor did classify correctly. The experimental results demonstrated that our approach performed well in real-time application.
Published in: 2013 22nd Wireless and Optical Communication Conference
Date of Conference: 16-18 May 2013
Date Added to IEEE Xplore: 02 December 2013
ISBN Information: