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Bart M. Ter Haar Romeny, W. Niessen, J. Weickert, P. Van Roermund, W. Van Enk, Antonio Lopez, et al. (1996). Orientation detection of trabecular bone.
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D. Lloret, Antonio Lopez, & Joan Serrat. (1997). Rigid Registration of CT and MR volumes based on Rothes creases.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & Michael G. Strintzis. (2004). 3D Gait Estimation from Monoscopic Video.
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Antonio Lopez, & Joan Serrat. (1997). Ridge/Valley-like structures: Creases, separatrices and drainage patterns.
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Antonio Lopez, Felipe Lumbreras, & Joan Serrat. (1997). Efficient computation of local creaseness. CVC, Bellaterra (Spain).
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Antonio Lopez, & Joan Serrat. (1998). Ridges and Valleys in Image Analysis.
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Antonio Lopez, Joan Serrat, J. Saludes, Cristina Cañero, Felipe Lumbreras, & T. Graf. (2005). Ridgeness for Detecting Lane Markings.
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Muhammad Anwer Rao, David Vazquez, & Antonio Lopez. (2011). Opponent Colors for Human Detection. In J. Vitria, J.M. Sanches, & M. Hernandez (Eds.), 5th Iberian Conference on Pattern Recognition and Image Analysis (Vol. 6669, pp. 363–370). LNCS. Berlin Heidelberg: Springer.
Abstract: 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.
Keywords: Pedestrian Detection; Color; Part Based Models
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Fadi Dornaika, & Angel Sappa. (2005). SFM for Planar Scenes: a Direct and Robust Approach.
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A. Restrepo, Angel Sappa, & M. Devy. (2005). Edge registration versus triangular mesh registration, a comparative study. Signal Processing: Image Communication 20: 853–868 (IF: 1.264).
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Fadi Dornaika, & Angel Sappa. (2005). Appearance-based 3D Face Tracker: An Evaluation Study.
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Antonio Lopez, Cristina Cañero, Joan Serrat, J. Saludes, Felipe Lumbreras, & T. Graf. (2005). Detection of lane markings based on ridgeness and RANSAC.
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Daniel Ponsa, Antonio Lopez, Felipe Lumbreras, Joan Serrat, & T. Graf. (2005). 3D Vehicle Sensor based on Monocular Vision.
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Daniel Ponsa, Antonio Lopez, Joan Serrat, Felipe Lumbreras, & T. Graf. (2005). Multiple Vehicle 3D Tracking Using an Unscented Kalman Filter.
Keywords: vehicle detection
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Fadi Dornaika, & Angel Sappa. (2006). Improving Appearance-Based 3D Face Tracking Using Sparse Stereo Data.
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