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Author David Masip; Jordi Vitria
Title (up) On the Nearest Neighbor Approach for Gender Recognition Type Miscellaneous
Year 2003 Publication In I. Aguilo, Ll. Valverde M.T. Escrig, editors. Artificial Intelligence Research and Development. IOS PRESS pp.178–188 Abbreviated Journal
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Address Amsterdam
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ MaV2003b Serial 387
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Author David Masip; Jordi Vitria
Title (up) On the Nearest Neighbor Approach for Gender Recognition Type Miscellaneous
Year 2003 Publication 6th Catalonian Conference on Artificial Intelligence Abbreviated Journal
Volume Issue Pages
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Abstract
Address Palma de Mallorca
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Publisher Place of Publication Editor
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ MaV2003c Serial 392
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Author Miquel Ferrer; F. Serratosa; Ernest Valveny
Title (up) On the Relation Between the Median Graph and the Maximum Common Subgraph of a Set of Graphs Type Book Chapter
Year 2007 Publication Abbreviated Journal
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Address Alicante (Spain)
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Notes DAG Approved no
Call Number DAG @ dag @ FSV2007 Serial 790
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Author Alejandro Cartas; Estefania Talavera; Petia Radeva; Mariella Dimiccoli
Title (up) On the Role of Event Boundaries in Egocentric Activity Recognition from Photostreams Type Miscellaneous
Year 2018 Publication Arxiv Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Event boundaries play a crucial role as a pre-processing step for detection, localization, and recognition tasks of human activities in videos. Typically, although their intrinsic subjectiveness, temporal bounds are provided manually as input for training action recognition algorithms. However, their role for activity recognition in the domain of egocentric photostreams has been so far neglected. In this paper, we provide insights of how automatically computed boundaries can impact activity recognition results in the emerging domain of egocentric photostreams. Furthermore, we collected a new annotated dataset acquired by 15 people by a wearable photo-camera and we used it to show the generalization capabilities of several deep learning based architectures to unseen users.
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Notes MILAB; no proj Approved no
Call Number Admin @ si @ CTR2018 Serial 3184
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Author Petia Radeva
Title (up) On the Role of Intravascular Ultrasound Image Analysis Type Miscellaneous
Year 2003 Publication Angiography and Plaque Imaging: Advanced Segmentation Techniques, CRC, pp.397–450, ISBN: 0849317401 Abbreviated Journal
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Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ Rad2003 Serial 402
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Author A. Pujol; Alex Caralps; Juan J. Villanueva
Title (up) On the suitability of pixel-outlier removal in face recognition. Type Miscellaneous
Year 2001 Publication Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:241–247 Abbreviated Journal
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Notes Approved no
Call Number ISE @ ise @ PCV2001 Serial 152
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Author Alex Gomez-Villa; Adrian Martin; Javier Vazquez; Marcelo Bertalmio; Jesus Malo
Title (up) On the synthesis of visual illusions using deep generative models Type Journal Article
Year 2022 Publication Journal of Vision Abbreviated Journal JOV
Volume 22(8) Issue 2 Pages 1-18
Keywords
Abstract Visual illusions expand our understanding of the visual system by imposing constraints in the models in two different ways: i) visual illusions for humans should induce equivalent illusions in the model, and ii) illusions synthesized from the model should be compelling for human viewers too. These constraints are alternative strategies to find good vision models. Following the first research strategy, recent studies have shown that artificial neural network architectures also have human-like illusory percepts when stimulated with classical hand-crafted stimuli designed to fool humans. In this work we focus on the second (less explored) strategy: we propose a framework to synthesize new visual illusions using the optimization abilities of current automatic differentiation techniques. The proposed framework can be used with classical vision models as well as with more recent artificial neural network architectures. This framework, validated by psychophysical experiments, can be used to study the difference between a vision model and the actual human perception and to optimize the vision model to decrease this difference.
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Notes LAMP; 600.161; 611.007 Approved no
Call Number Admin @ si @ GMV2022 Serial 3682
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Author Agata Lapedriza; David Masip; Jordi Vitria
Title (up) On the Use of External Face Features for Identity Verification Type Journal
Year 2006 Publication Journal of Multimedia, 1(4): 11–20 Abbreviated Journal
Volume 1 Issue 4 Pages 11-20
Keywords Face Verification, Computer Vision, Machine Learning
Abstract In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded.
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ LMV2006b Serial 708
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Author Agata Lapedriza; David Masip; Jordi Vitria
Title (up) On the Use of Independent Tasks for Face Recognition Type Conference Article
Year 2008 Publication IEEE Computer Society Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 1–6
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Area Expedition Conference CVPR
Notes OR; MV Approved no
Call Number BCNPCL @ bcnpcl @ LMV2008b Serial 1043
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke
Title (up) On the use of textural features for writer identification in old handwritten music scores Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 996 - 1000
Keywords
Abstract Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates.
Address Barcelona
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1520-5363 ISBN 978-1-4244-4500-4 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number DAG @ dag @ FLS2009b Serial 1223
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva
Title (up) On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging Type Conference Article
Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 67-74
Keywords classification; vessel border modelling; IVUS
Abstract IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
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Publisher IOS Press Place of Publication Amsterdam, The Netherlands Editor
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Notes IAM;MILAB Approved no
Call Number IAM @ iam @ HGR2005c Serial 1549
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Author Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva
Title (up) On Tracking Inside Groups Type Journal Article
Year 2010 Publication Machine Vision and Applications Abbreviated Journal MVA
Volume 21 Issue 2 Pages 113–127
Keywords
Abstract This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions.
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Publisher Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0932-8092 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ RGP2010 Serial 1158
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Author Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez
Title (up) On-board camera extrinsic parameter estimation Type Journal Article
Year 2006 Publication Electronics Letters Abbreviated Journal EL
Volume 42 Issue 13 Pages 745–746
Keywords
Abstract An efficient technique for real-time estimation of camera extrinsic parameters is presented. It is intended to be used on on-board vision systems for driving assistance applications. The proposed technique is based on the use of a commercial stereo vision system that does not need any visual feature extraction.
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Publisher IEE Place of Publication Editor
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Notes ADAS Approved no
Call Number ADAS @ adas @ SGD2006a Serial 655
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Author Zhijie Fang; David Vazquez; Antonio Lopez
Title (up) On-Board Detection of Pedestrian Intentions Type Journal Article
Year 2017 Publication Sensors Abbreviated Journal SENS
Volume 17 Issue 10 Pages 2193
Keywords pedestrian intention; ADAS; self-driving
Abstract Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw sensor data has a history of more than 15 years of research, with vision playing a central role.
During the last years, deep learning has boosted the accuracy of image-based pedestrian detectors.
However, detection is just the first step towards answering the core question, namely is the vehicle going to crash with a pedestrian provided preventive actions are not taken? Therefore, knowing as soon as possible if a detected pedestrian has the intention of crossing the road ahead of the vehicle is
essential for performing safe and comfortable maneuvers that prevent a crash. However, compared to pedestrian detection, there is relatively little literature on detecting pedestrian intentions. This paper aims to contribute along this line by presenting a new vision-based approach which analyzes the
pose of a pedestrian along several frames to determine if he or she is going to enter the road or not. We present experiments showing 750 ms of anticipation for pedestrians crossing the road, which at a typical urban driving speed of 50 km/h can provide 15 additional meters (compared to a pure pedestrian detector) for vehicle automatic reactions or to warn the driver. Moreover, in contrast with state-of-the-art methods, our approach is monocular, neither requiring stereo nor optical flow information.
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Notes ADAS; 600.085; 600.076; 601.223; 600.116; 600.118 Approved no
Call Number Admin @ si @ FVL2017 Serial 2983
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Author Daniel Ponsa; Joan Serrat; Antonio Lopez
Title (up) On-board image-based vehicle detection and tracking Type Journal Article
Year 2011 Publication Transactions of the Institute of Measurement and Control Abbreviated Journal TIM
Volume 33 Issue 7 Pages 783-805
Keywords vehicle detection
Abstract In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time.
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Notes ADAS Approved no
Call Number ADAS @ adas @ PSL2011 Serial 1413
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