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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Hernandez; Nadezhda Zlateva; Alexander Marinov; Miguel Reyes; Petia Radeva; Dimo Dimov; Sergio Escalera |
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Title |
Graph Cuts Optimization for Multi-Limb Human Segmentation in Depth Maps |
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Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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726-732 |
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We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α-β swap Graph-cuts algorithm. Moreover, depth of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches. |
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Portland; Oregon; June 2013 |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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MILAB;HuPBA |
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no |
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Admin @ si @ HZM2012b |
Serial |
2046 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Hernandez; Nadezhda Zlateva; Alexander Marinov; Miguel Reyes; Petia Radeva; Dimo Dimov; Sergio Escalera |
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Title |
Human Limb Segmentation in Depth Maps based on Spatio-Temporal Graph Cuts Optimization |
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Journal Article |
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Year |
2012 |
Publication |
Journal of Ambient Intelligence and Smart Environments |
Abbreviated Journal |
JAISE |
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Volume |
4 |
Issue |
6 |
Pages |
535-546 |
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Keywords |
Multi-modal vision processing; Random Forest; Graph-cuts; multi-label segmentation; human body segmentation |
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Abstract |
We present a framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α−β swap Graph-cuts algorithm. Moreover, depth values of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches. |
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1876-1364 |
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MILAB;HuPBA |
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Admin @ si @ HZM2012a |
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2006 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Hernandez; Sergio Escalera; Stan Sclaroff |
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Title |
Poselet-basedContextual Rescoring for Human Pose Estimation via Pictorial Structures |
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Journal Article |
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2016 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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118 |
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1 |
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49–64 |
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Contextual rescoring; Poselets; Human pose estimation |
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In this paper we propose a contextual rescoring method for predicting the position of body parts in a human pose estimation framework. A set of poselets is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body part hypotheses. A method is proposed for the automatic discovery of a compact subset of poselets that covers the different poses in a set of validation images while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for each body joint detection, given its relationship to detections of other body joints and mid-level parts in the image. This new score is incorporated in the pictorial structure model as an additional unary potential, following the recent work of Pishchulin et al. Experiments on two benchmarks show comparable results to Pishchulin et al. while reducing the size of the mid-level representation by an order of magnitude, reducing the execution time by 68 % accordingly. |
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Springer US |
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0920-5691 |
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HuPBA;MILAB; |
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Admin @ si @ HES2016 |
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2719 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Hernandez; Stan Sclaroff; Sergio Escalera |
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Title |
Contextual rescoring for Human Pose Estimation |
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Conference Article |
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Year |
2014 |
Publication |
25th British Machine Vision Conference |
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A contextual rescoring method is proposed for improving the detection of body joints of a pictorial structure model for human pose estimation. A set of mid-level parts is incorporated in the model, and their detections are used to extract spatial and score-related features relative to other body joint hypotheses. A technique is proposed for the automatic discovery of a compact subset of poselets that covers a set of validation images
while maximizing precision. A rescoring mechanism is defined as a set-based boosting classifier that computes a new score for body joint detections, given its relationship to detections of other body joints and mid-level parts in the image. This new score complements the unary potential of a discriminatively trained pictorial structure model. Experiments on two benchmarks show performance improvements when considering the proposed mid-level image representation and rescoring approach in comparison with other pictorial structure-based approaches. |
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Nottingham; UK; September 2013 |
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BMVC |
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HuPBA;MILAB |
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HSE2014 |
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2525 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez |
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Title |
Multilocal Methods for Ridge and Valley Delineation in Image Analysis. |
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2000 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Joan Serrat |
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ADAS |
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ADAS @ adas @ Lop2000 |
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174 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez |
![goto web page url](img/www.gif)
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Title |
Ridge/Valley-like structures: Creases, separatrices and drainage patterns |
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Miscellaneous |
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1997 |
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Computer vision on–line |
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CVC |
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ADAS |
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ADAS @ adas @ Lop1997 |
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488 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez |
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Title |
Pedestrian Detection Systems |
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Book Chapter |
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2018 |
Publication |
Wiley Encyclopedia of Electrical and Electronics Engineering |
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Pedestrian detection is a highly relevant topic for both advanced driver assistance systems (ADAS) and autonomous driving. In this entry, we review the ideas behind pedestrian detection systems from the point of view of perception based on computer vision and machine learning. |
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ADAS; 600.118 |
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no |
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Admin @ si @ Lop2018 |
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3230 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez |
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Title |
Computer Vision in Vehicle Technology: Land, Sea & Air |
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2017 |
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161-163 |
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Summary This chapter examines different vision-based commercial solutions for real-live problems related to vehicles. It is worth mentioning the recent astonishing performance of deep convolutional neural networks (DCNNs) in difficult visual tasks such as image classification, object recognition/localization/detection, and semantic segmentation. In fact,
different DCNN architectures are already being explored for low-level tasks such as optical flow and disparity computation, and higher level ones such as place recognition. |
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John Wiley & Sons, Ltd |
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978-1-118-86807-2 |
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ADAS; 600.118 |
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Admin @ si @ LIP2017a |
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2937 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; Atsushi Imiya; Tomas Pajdla; Jose Manuel Alvarez |
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Title |
Computer Vision in Vehicle Technology: Land, Sea & Air |
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Computer Vision in Vehicle Technology: Land, Sea & Air |
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A unified view of the use of computer vision technology for different types of vehicles
Computer Vision in Vehicle Technology focuses on computer vision as on-board technology, bringing together fields of research where computer vision is progressively penetrating: the automotive sector, unmanned aerial and underwater vehicles. It also serves as a reference for researchers of current developments and challenges in areas of the application of computer vision, involving vehicles such as advanced driver assistance (pedestrian detection, lane departure warning, traffic sign recognition), autonomous driving and robot navigation (with visual simultaneous localization and mapping) or unmanned aerial vehicles (obstacle avoidance, landscape classification and mapping, fire risk assessment).
The overall role of computer vision for the navigation of different vehicles, as well as technology to address on-board applications, is analysed. |
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978-1-118-86807-2 |
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DAG |
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Admin @ si @ LIP2017b |
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3049 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; Cristina Cañero; Joan Serrat; J. Saludes; Felipe Lumbreras; T. Graf |
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Title |
Detection of lane markings based on ridgeness and RANSAC |
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Miscellaneous |
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2005 |
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Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 733–738 |
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lane markings |
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Vienna (Austria) |
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ADAS |
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ADAS @ adas @ LCS2005 |
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588 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; David Lloret; Joan Serrat |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Creaseness measures for CT and MR image registration. |
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Miscellaneous |
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1998 |
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CVPR’98 , IEEE Computer Society, pgs.694–699 |
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Creases are a type of ridge/valley structures that can be characterized by local conditions. Therefore, creaseness refers to local ridgeness and valleyness. The curvature K of the level curves and the mean curvature kM of the level surfaces are good measures of creaseness for 2-d and 3-d images, respectively. However, the way they are computed gives rise to discontinuities, reducing their usefulness in many applications. We propose a new creaseness measure, based on these curvatures, that avoids the discontinuities. We demonstrate its usefulness in the registration of CT and MR brain volumes, from the same patient, by searching the maximum in the correlation of their creaseness responses (ridgeness from the CT and valleyness from the MR). Due to the high dimensionality of the space of transforms, the search is performed by a hierarchical approach combined with an optimization method at each level of the hierarchy |
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Santa Barbara, USA. |
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ADAS |
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ADAS @ adas @ LLS1998a |
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11 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; David Lloret; Joan Serrat; Juan J. Villanueva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Multilocal Creaseness Based on the Level-Set Extrinsic Curvarture. |
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Miscellaneous |
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2000 |
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Computer Vision and Image Understanding, Academic Press, 77(2):111–144. |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; David Vazquez; Gabriel Villalonga |
![goto web page url](img/www.gif)
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Title |
Data for Training Models, Domain Adaptation |
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2018 |
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Intelligent Vehicles. Enabling Technologies and Future Developments |
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395–436 |
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Driving simulator; hardware; software; interface; traffic simulation; macroscopic simulation; microscopic simulation; virtual data; training data |
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Simulation can enable several developments in the field of intelligent vehicles. This chapter is divided into three main subsections. The first one deals with driving simulators. The continuous improvement of hardware performance is a well-known fact that is allowing the development of more complex driving simulators. The immersion in the simulation scene is increased by high fidelity feedback to the driver. In the second subsection, traffic simulation is explained as well as how it can be used for intelligent transport systems. Finally, it is rather clear that sensor-based perception and action must be based on data-driven algorithms. Simulation could provide data to train and test algorithms that are afterwards implemented in vehicles. These tools are explained in the third subsection. |
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ADAS; 600.118 |
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Admin @ si @ LVV2018 |
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3047 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; Ernest Valveny; Juan J. Villanueva |
![goto web page url](img/www.gif)
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Title |
Real-time quality control of surgical material packaging by artificial vision |
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Journal Article |
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2005 |
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Assembly Automation |
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25 |
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3 |
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IF: 0.061) |
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ADAS;DAG |
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ADAS @ adas @ LVV2005 |
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552 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Antonio Lopez; Felipe Lumbreras; A. Martinez; Joan Serrat; Xavier Roca; Javier Varona; Jordi Vitria |
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Title |
Aplicaciones de la vision por computador a la industria. |
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Miscellaneous |
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1997 |
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ADAS;OR;ISE;MV |
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ADAS @ adas @ LLM1997b |
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50 |
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