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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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2009 |
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Journal of Mathematical Imaging and Vision |
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JMIV |
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34 |
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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 @ adas @ JSL2009a |
Serial |
1163 |
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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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Journal Article |
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2009 |
Publication |
Pattern Recognition |
Abbreviated Journal |
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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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach |
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Journal Article |
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Year |
2009 |
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International Journal of Electronic Commerce |
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14 |
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1 |
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89-108 |
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The paper presents a factorization-based approach to make predictions in recommender systems. These systems are widely used in electronic commerce to help customers find products according to their preferences. Taking into account the customer's ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the system. The proposed factorization-based approach uses all the information provided to compute the predicted ratings, in the same way as approaches based on Singular Value Decomposition (SVD). The main advantage of this technique versus SVD-based approaches is that it can deal with missing data. It also has a smaller computational cost. Experimental results with public data sets are provided to show that the proposed adapted factorization approach gives better predicted ratings than a widely used SVD-based approach. |
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1086-4415 |
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ADAS @ adas @ JSL2009b |
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1237 |
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Arnau Ramisa; Adriana Tapus; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
Robust Vision-Based Localization using Combinations of Local Feature Regions Detectors |
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2009 |
Publication |
Autonomous Robots |
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AR |
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27 |
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4 |
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373-385 |
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This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°.
In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization. |
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0929-5593 |
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Admin @ si @ RTA2009 |
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1245 |
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Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez |
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Title |
Rank Estimation in 3D Multibody Motion Segmentation |
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Journal Article |
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2008 |
Publication |
Electronic Letters |
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44 |
Issue |
4 |
Pages |
279-280 |
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A novel technique for rank estimation in 3D multibody motion segmentation is proposed. It is based on the study of the frequency spectra of moving rigid objects and does not use or assume a prior knowledge of the objects contained in the scene (i.e. number of objects and motion). The significance of rank estimation on multibody motion segmentation results is shown by using two motion segmentation algorithms over both synthetic and real data. |
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ADAS @ adas @ JSL2008a |
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939 |
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Joan Serrat; Ferran Diego; Felipe Lumbreras; Jose Manuel Alvarez; Antonio Lopez; C. Elvira |
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Title |
Dynamic Comparison of Headlights |
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2008 |
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Journal of Automobile Engineering |
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222 |
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5 |
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643–656 |
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video alignment |
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ADAS @ adas @ SDL2008a |
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958 |
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Author |
Yu Jie; Jaume Amores; N. Sebe; Petia Radeva; Tian Qi |
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Title |
Distance Learning for Similarity Estimation |
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2008 |
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IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(3):451–462 |
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ADAS;MILAB |
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ADAS @ adas @ JAS2008 |
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961 |
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Angel Sappa; Fadi Dornaika; Daniel Ponsa; David Geronimo; Antonio Lopez |
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Title |
An Efficient Approach to Onboard Stereo Vision System Pose Estimation |
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2008 |
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IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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9 |
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3 |
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476–490 |
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Camera extrinsic parameter estimation, ground plane estimation, onboard stereo vision system |
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This paper presents an efficient technique for estimating the pose of an onboard stereo vision system relative to the environment’s dominant surface area, which is supposed to be the road surface. Unlike previous approaches, it can be used either for urban or highway scenarios since it is not based on a specific visual traffic feature extraction but on 3-D raw data points. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact 2-D representation of the original 3-D data points is computed. Then, a RANdom SAmple Consensus (RANSAC) based least-squares approach is used to fit a plane to the road. Fast RANSAC fitting is obtained by selecting points according to a probability function that takes into account the density of points at a given depth. Finally, stereo camera height and pitch angle are computed related to the fitted road plane. The proposed technique is intended to be used in driverassistance systems for applications such as vehicle or pedestrian detection. Experimental results on urban environments, which are the most challenging scenarios (i.e., flat/uphill/downhill driving, speed bumps, and car’s accelerations), are presented. These results are validated with manually annotated ground truth. Additionally, comparisons with previous works are presented to show the improvements in the central processing unit processing time, as well as in the accuracy of the obtained results. |
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IEEE |
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ADAS @ adas @ SDP2008 |
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1000 |
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Fadi Dornaika; Angel Sappa |
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Evaluation of an Appearance-based 3D Face Tracker using Dense 3D Data |
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2008 |
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Machine Vision and Applications |
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19 |
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5-6 |
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427–441 |
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ADAS @ adas @ DoS2008b |
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1018 |
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Author |
Hugo Berti; Angel Sappa; Osvaldo Agamennoni |
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Title |
Improved Dynamic Window Approach by Using Lyapunov Stability Criteria |
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2008 |
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Latin American Applied Research |
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38 |
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4 |
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289–298 |
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ADAS @ adas @ BSA2008 |
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1056 |
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