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Muhammad Anwer Rao, David Vazquez and Antonio Lopez. 2011. Opponent Colors for Human Detection. In J. Vitria, J.M. Sanches and M. Hernandez, eds. 5th Iberian Conference on Pattern Recognition and Image Analysis. Berlin Heidelberg, Springer, 363–370. (LNCS.)
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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Muhammad Anwer Rao, David Vazquez and Antonio Lopez. 2011. Color Contribution to Part-Based Person Detection in Different Types of Scenarios. In P. Real, D.D., H. Molina, A. Berciano, W. Kropatsch, ed. 14th International Conference on Computer Analysis of Images and Patterns. Berlin Heidelberg, Springer, 463–470.
Abstract: Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution.
Keywords: Pedestrian Detection; Color
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Angel Sappa and M.A. Garcia. 2004. Hierarchical Clustering of 3D Objects and its Application to Minimum Distance Computation. IEEE International Conference on Robotics & Automation, 5287–5292, New Orleans, LA (USA), ISBN: 0–7803–8232–3.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis and Michael G. Strintzis. 2003. Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences. IEEE International Conference on Image Processing, Barcelona, Spain, September 2003.325–328.
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Angel Sappa and Mohammad Rouhani. 2009. Efficient Distance Estimation for Fitting Implicit Quadric Surfaces. 16th IEEE International Conference on Image Processing.3521–3524.
Abstract: This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach.
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Joan Serrat, J. Argemi and Juan J. Villanueva. 1991. Automatization of TW2 method using a knowledge-based image analysis system. VIth International Congress of Auxology..
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Angel Sappa and Boris X. Vintimilla. 2006. Edge Point Linking by Means of Global and Local Schemes. IEEE Int. Conf. on Signal-Image Technology and Internet-Based Systems, Hammamet, Tunisia, December 2006, pp. 551-560..
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Joan Serrat, Ferran Diego, Jose Manuel Alvarez and Felipe Lumbreras. 2007. Alignment of Videos Recorded from Moving Vehicles. in 14th International Conference on Image Analysis and Processing,.512–517.
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Angel Sappa, Fadi Dornaika, David Geronimo and Antonio Lopez. 2007. Efficient On-Board Stereo Vision Pose Estimation. Computer Aided Systems Theory, Selected paper from.1183–1190. (LNCS.)
Abstract: This paper presents an efficient technique for real time estimation of on-board stereo vision system pose. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the 3D road points. Fast RANSAC fitting is obtained by selecting points according to a probability distribution function that takes into account the density of points at a given depth. Finally, stereo camera position
and orientation—pose—is computed relative to the road plane. The proposed technique is intended to be used on driver assistance systems for applications such as obstacle or pedestrian detection. A real time performance is reached. Experimental results on several environments and comparisons with a previous work are presented.
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Angel Sappa, Fadi Dornaika, David Geronimo and Antonio Lopez. 2008. Registration-based Moving Object Detection from a Moving Camera. IROS2008 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles.65–69.
Abstract: This paper presents a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three stages. Initially, feature points are extracted and tracked through consecutive frames. Then, a RANSAC based approach is used for registering
two 3D point sets with known correspondences by means of the quaternion method. Finally, the computed 3D rigid displacement is used to map two consecutive frames into the same coordinate system. Moving objects correspond to those areas with large registration errors. Experimental results, in different scenarios, show the viability of the proposed approach.
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