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Author |
Marco Pedersoli |
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Title |
A Multiresolution Cascade for Human Detection |
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Miscellaneous |
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2008 |
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CVC Technical Report #126 |
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Barcelona, Spain |
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ISE |
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Admin @ si @ Ped2008 |
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1148 |
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Bhaskar Chakraborty |
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Title |
View-Invariant Human-Body Detection with Extension to Human Action Recognition using Component Wise HMM of Body Parts |
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2008 |
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CVC Technical Report #123 |
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Admin @ si @ Cha2008 |
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1149 |
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Mohammad Rouhani |
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Title |
3D Data Fitting and Tracking for Real Time Applications |
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2009 |
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CVC Technical Report |
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138 |
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138 |
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Barcelona, Spain |
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Master's thesis |
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invisible;ADAS |
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no |
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Admin @ si @ Rou2009 |
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1150 |
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Author |
Pierluigi Casale |
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Title |
Social Environment Description from Data Collected with a Wearable Device |
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2008 |
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CVC Technical Report #124 |
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Admin @ si @ Cas2008 |
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1151 |
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Author |
Fadi Dornaika; Angel Sappa |
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Title |
A Featureless and Stochastic Approach to On-board Stereo Vision System Pose |
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Journal Article |
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Year |
2009 |
Publication |
Image and Vision Computing |
Abbreviated Journal |
IMAVIS |
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Volume |
27 |
Issue |
9 |
Pages |
1382–1393 |
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On-board stereo vision system; Pose estimation; Featureless approach; Particle filtering; Image warping |
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This paper presents a direct and stochastic technique for real-time estimation of on-board stereo head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the stream of stereo pairs’ brightness. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the estimated parameters. The proposed technique can be used with a driver assistance applications as well as with augmented reality applications. Extended experiments on urban environments with different road geometries are presented. Comparisons with a 3D data-based approach are presented. Moreover, we provide a performance study aiming at evaluating the accuracy of the proposed approach. |
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ADAS |
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no |
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ADAS @ adas @ DoS2009b |
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1152 |
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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Separability of Ternary Codes for Sparse Designs of Error-Correcting Output Codes |
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Journal Article |
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2009 |
Publication |
Pattern Recognition Letters |
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PRL |
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30 |
Issue |
3 |
Pages |
285–297 |
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Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new Sparse Random coding matrix with ternary distance maximization. The results on the UCI Repository and in a real speed traffic categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied. |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2009a |
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1153 |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Title |
Psychophysical measurements to model inter-colour regions of colour-naming space |
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Journal Article |
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Year |
2009 |
Publication |
Journal of Imaging Science and Technology |
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Volume |
53 |
Issue |
3 |
Pages |
031106 (8 pages) |
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image processing; Analysis |
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JCR Impact Factor 2009: 0.391
In this paper, we present a fuzzy-set of parametric functions which segment the CIE lab space into eleven regions which correspond to the group of common universal categories present in all evolved languages as identified by anthropologists and linguists. The set of functions is intended to model a color-name assignment task by humans and differs from other models in its emphasis on the inter-color boundary regions, which were explicitly measured by means of a psychophysics experiment. In our particular implementation, the CIE lab space was segmented into eleven color categories using a Triple Sigmoid as the fuzzy sets basis, whose parameters are included in this paper. The model’s parameters were adjusted according to the psychophysical results of a yes/no discrimination paradigm where observers had to choose (English) names for isoluminant colors belonging to regions in-between neighboring categories. These colors were presented on a calibrated CRT monitor (14-bit x 3 precision). The experimental results show that inter- color boundary regions are much less defined than expected and color samples other than those near the most representatives are needed to define the position and shape of boundaries between categories. The extended set of model parameters is given as a table. |
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CIC |
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no |
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CAT @ cat @ PBV2009 |
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1157 |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
An iterative multiresolution scheme for SFM with missing data |
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Journal Article |
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Year |
2009 |
Publication |
Journal of Mathematical Imaging and Vision |
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JMIV |
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34 |
Issue |
3 |
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240–258 |
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Several techniques have been proposed for tackling the Structure from Motion problem through factorization in the case of missing data. However, when the percentage of unknown data is high, most of them may not perform as well as expected. Focussing on this problem, an iterative multiresolution scheme, which aims at recovering missing entries in the originally given input matrix, is proposed. Information recovered following a coarse-to-fine strategy is used for filling in the missing entries. The objective is to recover, as much as possible, missing data in the given matrix.
Thus, when a factorization technique is applied to the partially or totally filled in matrix, instead of to the originally given input one, better results will be obtained. An evaluation study about the robustness to missing and noisy data is reported.
Experimental results obtained with synthetic and real video sequences are presented to show the viability of the proposed approach. |
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ADAS |
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no |
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ADAS @ adas @ JSL2009a |
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1163 |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa |
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Title |
Median Graphs: A Genetic Approach based on New Theoretical Properties |
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2009 |
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Pattern Recognition |
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PR |
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42 |
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9 |
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2003–2012 |
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Median graph; Genetic search; Maximum common subgraph; Graph matching; Structural pattern recognition |
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Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present two major contributions. On one side, and from a theoretical point of view, we show new theoretical properties of the median graph. On the other side, using these new properties, we present a new approximate algorithm based on the genetic search, that improves the computation of the median graph. Finally, we perform a set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity. With these results, we show how the concept of the median graph can be used in real applications and leaves the box of the only-theoretical concepts, demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. |
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DAG |
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DAG @ dag @ FVS2009b |
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1167 |
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Daniel Ponsa; Antonio Lopez |
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Title |
Variance reduction techniques in particle-based visual contour Tracking |
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2009 |
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Pattern Recognition |
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PR |
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42 |
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11 |
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2372–2391 |
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Contour tracking; Active shape models; Kalman filter; Particle filter; Importance sampling; Unscented particle filter; Rao-Blackwellization; Partitioned sampling |
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This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done. |
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ADAS @ adas @ PoL2009a |
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1168 |
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Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez |
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Generation of Augmented Video Sequences Combining Behavioral Animation and Multi Object Tracking |
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2009 |
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Computer Animation and Virtual Worlds |
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20 |
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4 |
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473–489 |
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In this paper we present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior-based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd.
We present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. © 2009 Wiley Periodicals, Inc. |
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ISE @ ise @ BFR2009 |
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1170 |
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Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich |
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Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset |
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2009 |
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Journal of Imaging Science and Technology |
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53 |
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3 |
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031105–9 |
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The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene. |
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CAT @ cat @ VPV2009a |
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1171 |
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Marçal Rusiñol; Agnes Borras; Josep Llados |
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Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images |
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2010 |
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Pattern Recognition Letters |
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PRL |
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31 |
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3 |
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188–201 |
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Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings |
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This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results. |
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Elsevier |
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DAG @ dag @ RBL2010 |
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1177 |
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Sergio Escalera; Alicia Fornes; O. Pujol; Petia Radeva; Gemma Sanchez; Josep Llados |
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Blurred Shape Model for Binary and Grey-level Symbol Recognition |
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2009 |
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Pattern Recognition Letters |
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30 |
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15 |
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1424–1433 |
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Many symbol recognition problems require the use of robust descriptors in order to obtain rich information of the data. However, the research of a good descriptor is still an open issue due to the high variability of symbols appearance. Rotation, partial occlusions, elastic deformations, intra-class and inter-class variations, or high variability among symbols due to different writing styles, are just a few problems. In this paper, we introduce a symbol shape description to deal with the changes in appearance that these types of symbols suffer. The shape of the symbol is aligned based on principal components to make the recognition invariant to rotation and reflection. Then, we present the Blurred Shape Model descriptor (BSM), where new features encode the probability of appearance of each pixel that outlines the symbols shape. Moreover, we include the new descriptor in a system to deal with multi-class symbol categorization problems. Adaboost is used to train the binary classifiers, learning the BSM features that better split symbol classes. Then, the binary problems are embedded in an Error-Correcting Output Codes framework (ECOC) to deal with the multi-class case. The methodology is evaluated on different synthetic and real data sets. State-of-the-art descriptors and classifiers are compared, showing the robustness and better performance of the present scheme to classify symbols with high variability of appearance. |
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HuPBA; DAG; MILAB |
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BCNPCL @ bcnpcl @ EFP2009a |
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1180 |
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Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva |
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Text Detection in Urban Scenes (video sample) |
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2009 |
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12th International Conference of the Catalan Association for Artificial Intelligence |
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202 |
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35–44 |
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Abstract. Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches |
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Cardona (Spain) |
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978-1-60750-061-2 |
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CCIA |
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OR;MILAB;HuPBA;MV |
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BCNPCL @ bcnpcl @ EBV2009 |
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1181 |
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