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Author |
Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Title |
Monocular 3D Human Body Reconstruction Towards Depth Augmentation of Television Sequences |
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Conference Article |
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Year |
2003 |
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IEEE International Conference on Image Processing, Barcelona, Spain, September 2003 |
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325-328 |
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Barcelona |
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ADAS |
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no |
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ADAS @ adas @ SAM2003 |
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418 |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
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Title |
Monocular Depth-based Background Estimation |
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Conference Article |
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Year |
2012 |
Publication |
7th International Conference on Computer Vision Theory and Applications |
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323-328 |
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In this paper, we address the problem of reconstructing the background of a scene from a video sequence with occluding objects. The images are taken by hand-held cameras. Our method composes the background by selecting the appropriate pixels from previously aligned input images. To do that, we minimize a cost function that penalizes the deviations from the following assumptions: background represents objects whose distance to the camera is maximal, and background objects are stationary. Distance information is roughly obtained by a supervised learning approach that allows us to distinguish between close and distant image regions. Moving foreground objects are filtered out by using stationariness and motion boundary constancy measurements. The cost function is minimized by a graph cuts method. We demonstrate the applicability of our approach to recover an occlusion-free background in a set of sequences. |
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Roma |
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VISAPP |
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ADAS |
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no |
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Admin @ si @ CPL2012b; ADAS @ adas @ cpl2012e |
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2012 |
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Author |
Dennis G.Romero; Anselmo Frizera; Angel Sappa; Boris X. Vintimilla; Teodiano F.Bastos |
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Title |
A predictive model for human activity recognition by observing actions and context |
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Conference Article |
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Year |
2015 |
Publication |
Advanced Concepts for Intelligent Vision Systems, Proceedings of 16th International Conference, ACIVS 2015 |
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9386 |
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323-333 |
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This paper presents a novel model to estimate human activities — a human activity is defined by a set of human actions. The proposed approach is based on the usage of Recurrent Neural Networks (RNN) and Bayesian inference through the continuous monitoring of human actions and its surrounding environment. In the current work human activities are inferred considering not only visual analysis but also additional resources; external sources of information, such as context information, are incorporated to contribute to the activity estimation. The novelty of the proposed approach lies in the way the information is encoded, so that it can be later associated according to a predefined semantic structure. Hence, a pattern representing a given activity can be defined by a set of actions, plus contextual information or other kind of information that could be relevant to describe the activity. Experimental results with real data are provided showing the validity of the proposed approach. |
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Catania; Italy; October 2015 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-25902-4 |
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ACIVS |
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ADAS; 600.076 |
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no |
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Admin @ si @ RFS2015 |
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2661 |
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Author |
David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Real-time Object Segmentation using a Bag of Features Approach |
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Conference Article |
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Year |
2010 |
Publication |
13th International Conference of the Catalan Association for Artificial Intelligence |
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220 |
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Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
321–329 |
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Keywords |
Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors |
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In this paper, we propose an object segmentation framework, based on the popular bag of features (BoF), which can process several images per second while achieving a good segmentation accuracy assigning an object category to every pixel of the image. We propose an efficient color descriptor to complement the information obtained by a typical gradient-based local descriptor. Results show that color proves to be a useful cue to increase the segmentation accuracy, specially in large homogeneous regions. Then, we extend the Hierarchical K-Means codebook using the recently proposed Vector of Locally Aggregated Descriptors method. Finally, we show that the BoF method can be easily parallelized since it is applied locally, thus the time necessary to process an image is further reduced. The performance of the proposed method is evaluated in the standard PASCAL 2007 Segmentation Challenge object segmentation dataset. |
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IOS Press Amsterdam, |
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In R.Alquezar, A.Moreno, J.Aguilar. |
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9781607506423 |
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CCIA |
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ADAS |
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no |
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Admin @ si @ ARL2010b |
Serial |
1417 |
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Permanent link to this record |
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Author |
Fernando Barrera; Felipe Lumbreras; Angel Sappa |
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Title |
Evaluation of Similarity Functions in Multimodal Stereo |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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Volume |
7324 |
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I |
Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
320-329 |
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Aveiro, Portugal |
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Abstract |
This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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ADAS |
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no |
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Call Number |
BLS2012a |
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2014 |
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Permanent link to this record |
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Author |
Carme Julia; Angel Sappa; Felipe Lumbreras; Antonio Lopez |
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Title |
Recovery of Surface Normals and Reflectance from Different Lighting Conditions |
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Conference Article |
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Year |
2008 |
Publication |
5th International Conference on Image Analysis and Recognition |
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Volume |
5112 |
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315–325 |
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ADAS |
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ADAS @ adas @ JSL2008c |
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1014 |
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Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
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Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
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Conference Article |
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Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
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Volume |
6611 |
Issue |
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Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
314-325 |
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Abstract |
In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. |
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Dublin, Ireland |
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Springer |
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Berlin |
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P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
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978-3-642-20160-8 |
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ECIR |
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Notes |
DAG; RV;ADAS |
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no |
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Admin @ si @ RAK2011 |
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1737 |
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Permanent link to this record |
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Author |
Miguel Oliveira; Angel Sappa; V. Santos |
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Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
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Pages ![sorted by First Page field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
299-303 |
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The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
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Address |
Alcalá de Henares |
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IEEE Xplore |
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ISSN |
1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
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no |
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Admin @ si @ OSS2012b |
Serial |
2021 |
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Permanent link to this record |
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Author |
Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Comparing Combinations of Feature Regions for Panoramic VSLAM |
Type |
Conference Article |
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Year |
2007 |
Publication |
4th International Conference on Informatics in Control, Automation and Robotics |
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292–297 |
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Angers (France) |
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ICINCO |
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RV;ADAS |
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no |
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Admin @ si @ RLA2007 |
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900 |
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Author |
Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras |
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Title |
Robust Lane Lines Detection and Quantitative Assessment |
Type |
Conference Article |
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Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis |
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4477 |
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274–281 |
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Keywords |
lane markings |
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Address |
Girona (Spain) |
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J. Marti et al |
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IbPRIA |
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ADAS |
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no |
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ADAS @ adas @ LSC2007 |
Serial |
881 |
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