Object detection using non-redundant local Binary Patterns

Authors

Duc Thanh Nguyen, University of WollongongFollow
zhimin Zong, University of Wollongong
Philip Ogunbona, University of WollongongFollow
Wanqing Li, University of WollongongFollow

RIS ID

35208

Publication Details

Nguyen, D., Zong, z., Ogunbona, P. & Li, W. (2010). Object detection using non-redundant local Binary Patterns. Proceedings of 2010 IEEE 17th International Conference on Image Processing (pp. 4609-4612). New York, NY, USA: IEEE.

Abstract

Local Binary Pattern (LBP) as a descriptor, has been successfully used in various object recognition tasks because of its discriminative property and computational simplicity. In this paper a variant of the LBP referred to as Non-Redundant Local Binary Pattern (NRLBP) is introduced and its application for object detection is demonstrated. Compared with the original LBP descriptor, the NRLBP has advantage of providing a more compact description of object’s appearance. Furthermore, the NRLBP is more discriminative since it reflects the relative contrast between the background and foreground. The proposed descriptor is employed to encode human’s appearance in a human detection task. Experimental results show that the NRLBP is robust and adaptive with changes of the background and foreground and also outperforms the original LBP in detection task.