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Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
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Title  |
Efficient Object Pixel-Level Categorization using Bag of Features: Advances in Visual Computing |
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Conference Article |
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2009 |
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5th International Symposium on Visual Computing |
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5875 |
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44–55 |
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In this paper we present a pixel-level object categorization method suitable to be applied under real-time constraints. Since pixels are categorized using a bag of features scheme, the major bottleneck of such an approach would be the feature pooling in local histograms of visual words. Therefore, we propose to bypass this time-consuming step and directly obtain the score from a linear Support Vector Machine classifier. This is achieved by creating an integral image of the components of the SVM which can readily obtain the classification score for any image sub-window with only 10 additions and 2 products, regardless of its size. Besides, we evaluated the performance of two efficient feature quantization methods: the Hierarchical K-Means and the Extremely Randomized Forest. All experiments have been done in the Graz02 database, showing comparable, or even better results to related work with a lower computational cost. |
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Las Vegas, USA |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-10330-8 |
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ISVC |
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ADAS |
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Admin @ si @ ATR2009a |
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1246 |
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Author |
Angel Sappa; Mohammad Rouhani |
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Title |
Efficient Distance Estimation for Fitting Implicit Quadric Surfaces |
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Conference Article |
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Year |
2009 |
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16th IEEE International Conference on Image Processing |
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3521–3524 |
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This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach. |
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Cairo, Egypt |
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1522-4880 |
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978-1-4244-5653-6 |
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ICIP |
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ADAS @ adas @ SaR2009 |
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1232 |
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Author |
Angel Sappa; Boris X. Vintimilla |
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Title |
Edge Point Linking by Means of Global and Local Schemes |
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Conference Article |
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2006 |
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IEEE Int. Conf. on Signal-Image Technology and Internet-Based Systems, Hammamet, Tunisia, December 2006, pp. 551-560. |
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Hammamet (Tunisia) |
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ADAS |
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ADAS @ adas @ SaV2006 |
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722 |
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Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; M.Gomez; Antonio Tovar; L.Cano; C.Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
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Title |
Ecografia Intracoronària: Segmentació Automàtica de area de la llum |
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Conference Article |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ RMF2002 |
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1638 |
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Author |
Ariel Amato; Angel Sappa; Alicia Fornes; Felipe Lumbreras; Josep Llados |
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Title |
Divide and Conquer: Atomizing and Parallelizing A Task in A Mobile Crowdsourcing Platform |
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Conference Article |
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2013 |
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2nd International ACM Workshop on Crowdsourcing for Multimedia |
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21-22 |
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In this paper we present some conclusions about the advantages of having an efficient task formulation when a crowdsourcing platform is used. In particular we show how the task atomization and distribution can help to obtain results in an efficient way. Our proposal is based on a recursive splitting of the original task into a set of smaller and simpler tasks. As a result both more accurate and faster solutions are obtained. Our evaluation is performed on a set of ancient documents that need to be digitized. |
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Barcelona; October 2013 |
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978-1-4503-2396-3 |
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CrowdMM |
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ADAS; ISE; DAG; 600.054; 600.055; 600.045; 600.061; 602.006 |
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Admin @ si @ SLA2013 |
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2335 |
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Author |
Diego Porres |
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Title |
Discriminator Synthesis: On reusing the other half of Generative Adversarial Networks |
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Conference Article |
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2021 |
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Machine Learning for Creativity and Design, Neurips Workshop |
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Generative Adversarial Networks have long since revolutionized the world of computer vision and, tied to it, the world of art. Arduous efforts have gone into fully utilizing and stabilizing training so that outputs of the Generator network have the highest possible fidelity, but little has gone into using the Discriminator after training is complete. In this work, we propose to use the latter and show a way to use the features it has learned from the training dataset to both alter an image and generate one from scratch. We name this method Discriminator Dreaming, and the full code can be found at this https URL. |
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Virtual; December 2021 |
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NEURIPSW |
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ADAS; 601.365 |
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Admin @ si @ Por2021 |
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3597 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Michael Felsberg; J.Laaksonen |
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Title |
Deep semantic pyramids for human attributes and action recognition |
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Conference Article |
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2015 |
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Image Analysis, Proceedings of 19th Scandinavian Conference , SCIA 2015 |
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9127 |
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341-353 |
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Action recognition; Human attributes; Semantic pyramids |
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Describing persons and their actions is a challenging problem due to variations in pose, scale and viewpoint in real-world images. Recently, semantic pyramids approach [1] for pose normalization has shown to provide excellent results for gender and action recognition. The performance of semantic pyramids approach relies on robust image description and is therefore limited due to the use of shallow local features. In the context of object recognition [2] and object detection [3], convolutional neural networks (CNNs) or deep features have shown to improve the performance over the conventional shallow features.
We propose deep semantic pyramids for human attributes and action recognition. The method works by constructing spatial pyramids based on CNNs of different part locations. These pyramids are then combined to obtain a single semantic representation. We validate our approach on the Berkeley and 27 Human Attributes datasets for attributes classification. For action recognition, we perform experiments on two challenging datasets: Willow and PASCAL VOC 2010. The proposed deep semantic pyramids provide a significant gain of 17.2%, 13.9%, 24.3% and 22.6% compared to the standard shallow semantic pyramids on Berkeley, 27 Human Attributes, Willow and PASCAL VOC 2010 datasets respectively. Our results also show that deep semantic pyramids outperform conventional CNNs based on the full bounding box of the person. Finally, we compare our approach with state-of-the-art methods and show a gain in performance compared to best methods in literature. |
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Denmark; Copenhagen; June 2015 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-19664-0 |
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SCIA |
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LAMP; 600.068; 600.079;ADAS |
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Admin @ si @ KRW2015b |
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2672 |
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Author |
Jiaolong Xu; Sebastian Ramos; David Vazquez; Antonio Lopez |
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Title |
DA-DPM Pedestrian Detection |
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Conference Article |
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2013 |
Publication |
ICCV Workshop on Reconstruction meets Recognition |
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Domain Adaptation; Pedestrian Detection |
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ICCVW-RR |
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ADAS |
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Admin @ si @ XRV2013 |
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2569 |
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Author |
Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa |
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Title |
Cross-spectral Stereo Correspondence using Dense Flow Fields |
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Conference Article |
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2014 |
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9th International Conference on Computer Vision Theory and Applications |
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3 |
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613-617 |
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Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum |
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This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. |
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Lisboa; Portugal; January 2014 |
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VISAPP |
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ADAS; 600.055; 600.076 |
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Admin @ si @ OAV2014 |
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2477 |
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Author |
M. Cruz; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Ricardo Toledo; Angel Sappa |
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Title |
Cross-spectral image registration and fusion: an evaluation study |
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Conference Article |
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2015 |
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2nd International Conference on Machine Vision and Machine Learning |
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multispectral imaging; image registration; data fusion; infrared and visible spectra |
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This paper presents a preliminary study on the registration and fusion of cross-spectral imaging. The objective is to evaluate the validity of widely used computer vision approaches when they are applied at different
spectral bands. In particular, we are interested in merging images from the infrared (both long wave infrared: LWIR and near infrared: NIR) and visible spectrum (VS). Experimental results with different data sets are presented. |
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Barcelona; July 2015 |
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MVML |
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ADAS; 600.076 |
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Admin @ si @ CAV2015 |
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2629 |
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