TY - CONF AU - Muhammad Anwer Rao AU - David Vazquez AU - Antonio Lopez A2 - IbPRIA ED - J. Vitria ED - J.M. Sanches ED - M. Hernandez PY - 2011// TI - Opponent Colors for Human Detection T2 - LNCS BT - 5th Iberian Conference on Pattern Recognition and Image Analysis T3 - Lecture Notes on Computer Science SP - 363 EP - 370 VL - 6669 PB - Springer CY - Berlin Heidelberg KW - Pedestrian Detection KW - Color KW - Part Based Models N2 - Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. SN - 0302-9743 SN - 978-3-642-21256-7 L1 - http://refbase.cvc.uab.es/files/AVL2011b.pdf UR - http://dx.doi.org/10.1007/978-3-642-21257-4_45 N1 - ADAS ID - Muhammad Anwer Rao2011 ER -