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B. Moghaddam, David Guillamet, & Jordi Vitria. (2003). Local Appearance-Based Models using High-Order Statistics of Image Features. In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR).
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Daniel Ponsa, & Xavier Roca. (2003). Multiple Model Approach to Deformable Shape Tracking. In 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 (Vol. 2652, pp. 782–792). LNCS.
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Angel Sappa, Niki Aifanti, Sotiris Malassiotis, & Michael G. Strintzis. (2003). Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences. In IEEE International Conference on Image Processing, Barcelona, Spain, September 2003 (pp. 325–328).
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Anna Salvatella, Maria Vanrell, & Ramon Baldrich. (2003). Subtexture Components for Texture Description. In 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 (Vol. 2652, pp. 884–892). LNCS.
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Anna Salvatella, Maria Vanrell, & Juan J. Villanueva. (2003). Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis. In 3rd International Workshop on Texture Synthesis and Analysis, (77–82).
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Angel Sappa, & M.A. Garcia. (2004). Hierarchical Clustering of 3D Objects and its Application to Minimum Distance Computation. In IEEE International Conference on Robotics & Automation, 5287–5292, New Orleans, LA (USA), ISBN: 0–7803–8232–3.
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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. In Biophysics and Molecular Biology, International Biophysics Congress. Volume 65, pgs. P–H5–43.
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David Lloret, Antonio Lopez, & Joan Serrat. (1997). Rigid Registration of CT and MR volumes based on Rothes creases. In (SNRFAI’97) 7th Spanish National Symposium on Pattern Recognition and Image Analysis (pp. 1–6).
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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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Joel Barajas, Jaume Garcia, Francesc Carreras, Sandra Pujades, & Petia Radeva. (2005). Angle Images Using Gabor Filters in Cardiac Tagged MRI. In Proceeding of the 2005 conference on Artificial Intelligence Research and Development (pp. 107–114). Amsterdam, The Netherlands: IOS Press.
Abstract: Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results.
Keywords: Angle Images, Gabor Filters, Harp, Tagged Mri
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Anton Cervantes, Gemma Sanchez, Josep Llados, Agnes Borras, & A. Rodriguez. (2005). Biometric Recognition Based on Line Shape Descriptors. In Sixth IAPR International Workshop on Graphics Recognition (GREC 2005) (335–344).
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Jaume Garcia, Joel Barajas, Francesc Carreras, Sandra Pujades, & Petia Radeva. (2005). An intuitive validation technique to compare local versus global tagged MRI analysis. In Computers In Cardiology (Vol. 32, 29–32).
Abstract: Myocardium appears as a uniform tissue that seen in convectional Magnetic Resonance Images (MRI) shows just the contractile part of its movement. MR Tagging is a unique imaging technique that prints a grid over the tissue which moves according to the underlying movement of the myocardium revealing the true deformation of the cardiac muscle. Optical flow techniques based on spectral information estimate tissue displacement by analyzing information encoded in the phase maps which can be obtained using, local (Gabor) and global (HARP) methods. In this paper we compare both in synthetic and real Tagged MR sequences. We conclude that local method is slightly more accurate than the global one. On the other hand, global method is more efficient as it is much faster and less parameters have to be taken into account
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Fernando Lopez, J.M. Valiente, Ramon Baldrich, & Maria Vanrell. (2005). Fast surface grading using color statistics in the CIELab space. In Pattern Recognition and Image Analysis. IbPRIA 2005 (Vol. LNCS 3523, pp. 66–673).
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Carme Julia, Angel Sappa, Felipe Lumbreras, Joan Serrat, & Antonio Lopez. (2006). Factorization with Missing and Noisy Data. In 6th International Conference on Computational Science (Vol. LNCS 3991, 555–562).
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Angel Sappa, David Geronimo, Fadi Dornaika, & Antonio Lopez. (2006). Real Time Vehicle Pose Using On-Board Stereo Vision System. In International Conference on Image Analysis and Recognition (205–216).
Abstract: This paper presents a robust technique for a real time estimation of both camera’s position and orientation—referred as pose. A commercial stereo vision system is used. Unlike previous approaches, it can be used either for urban or highway scenarios. The proposed technique consists of two stages. Initially, a compact 2D representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the road. At the same time,
relative camera’s position and orientation are computed. The proposed technique is intended to be used on a driving assistance scheme for applications such as obstacle or pedestrian detection. Experimental results on urban environments with different road geometries are presented.
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