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Author Antonio Hernandez; Miguel Reyes; Sergio Escalera; Petia Radeva
Title (down) Spatio-Temporal GrabCut human segmentation for face and pose recovery Type Conference Article
Year 2010 Publication IEEE International Workshop on Analysis and Modeling of Faces and Gestures Abbreviated Journal
Volume Issue Pages 33–40
Keywords
Abstract In this paper, we present a full-automatic Spatio-Temporal GrabCut human segmentation methodology. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model for seed initialization. Spatial information is included by means of Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, human segmentation is combined with Shape and Active Appearance Models to perform full face and pose recovery. Results over public data sets as well as proper human action base show a robust segmentation and recovery of both face and pose using the presented methodology.
Address San Francisco; CA; USA; June 2010
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 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference AMFG
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ HRE2010 Serial 1362
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Author David Geronimo; Antonio Lopez
Title (down) Sistema de deteccion de peatones Type Miscellaneous
Year 2010 Publication UAB Divulga Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Durante la próxima década, los sistemas de protección de peatones jugarán un papel fundamental en el reto de mejorar la seguridad viaria. El objetivo principal de estos sistemas, detectar peatones en entornos urbanos, implica procesar imágenes de escenas exteriores desde una plataforma móvil para buscar objetos de aspecto variable como son las personas. Dadas estas dificultades, estos sistemas hacen uso de las últimas técnicas de visión por computador. Esta propuesta consiste en un sistema de tres módulos basado tanto en información 2D como en 3D. El primer módulo utiliza información 3D para hacer una estimación de los parámetros de la carretera y seleccionar regiones de interés que serán analizadas después. El segundo módulo utiliza un clasificador de ventanas 2D para etiquetar las mencionadas regiones como peatón o no peatón. El módulo final vuelve a utilizar de nuevo la información 3D para verificar las regiones clasificadas y, con información 2D, refinar los resultados finales. Los resultados experimentales son positivos tanto en rendimiento como en tiempo de cómputo.
Address Bellaterra (Spain)
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 ISBN Medium
Area Expedition Conference
Notes spreading;ADAS Approved no
Call Number ADAS @ adas @ GeL2010b Serial 1473
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Author Fadi Dornaika; Bogdan Raducanu
Title (down) Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario Type Conference Article
Year 2010 Publication 1st International Workshop on Computer Vision for Human-Robot Interaction Abbreviated Journal
Volume Issue Pages 32–39
Keywords 1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010
Abstract This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods.
Address San Francisco; CA; USA; June 2010
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 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference CVPRW
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010a Serial 1309
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Author Michal Drozdzal; Laura Igual; Jordi Vitria; Petia Radeva; Carolina Malagelada; Fernando Azpiroz
Title (down) SIFT flow-based Sequences Alignment Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 7–8
Keywords
Abstract
Address Girona, Spain
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 ISBN Medium
Area Expedition Conference MICCAT
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIV2010 Serial 1475
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Author Santiago Segui; Michal Drozdzal; Petia Radeva; Jordi Vitria
Title (down) Severe Motility Diagnosis using WCE Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 45–46
Keywords
Abstract
Address Girona, Spain
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 ISBN Medium
Area Expedition Conference MICCAT
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ SDR2010 Serial 1478
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Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title (down) Seal Object Detection in Document Images using GHT of Local Component Shapes Type Conference Article
Year 2010 Publication 10th ACM Symposium On Applied Computing Abbreviated Journal
Volume Issue Pages 23–27
Keywords
Abstract Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents.
Address Sierre, Switzerland
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 ISBN Medium
Area Expedition Conference SAC
Notes DAG Approved no
Call Number DAG @ dag @ RPL2010a Serial 1291
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Author Eduard Vazquez; Theo Gevers; M. Lucassen; Joost Van de Weijer; Ramon Baldrich
Title (down) Saliency of Color Image Derivatives: A Comparison between Computational Models and Human Perception Type Journal Article
Year 2010 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A
Volume 27 Issue 3 Pages 613–621
Keywords
Abstract In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%.
Address
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 ISBN Medium
Area Expedition Conference
Notes ISE;CIC Approved no
Call Number CAT @ cat @ VGL2010 Serial 1275
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas
Title (down) Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 3 Pages 229–241
Keywords
Abstract One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.
Address
Corporate Author Thesis
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 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; IF 2009: 1,213 Approved no
Call Number DAG @ dag @ FLS2010a Serial 1288
Permanent link to this record
 
 
Author Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez
Title (down) Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns Type Journal Article
Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ
Volume Issue Pages 7
Keywords
Abstract Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications.
Address
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 1110-8657 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ AMR2010 Serial 1463
Permanent link to this record
 
 
Author Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras; T. Graf
Title (down) Robust lane markings detection and road geometry computation Type Journal Article
Year 2010 Publication International Journal of Automotive Technology Abbreviated Journal IJAT
Volume 11 Issue 3 Pages 395–407
Keywords lane markings
Abstract Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings. A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic video sequences for which road geometry and vehicle trajectory ground truth are known.
Address
Corporate Author Thesis
Publisher The Korean Society of Automotive Engineers Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1229-9138 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ LSC2010 Serial 1300
Permanent link to this record
 
 
Author Mohammad Rouhani; Angel Sappa
Title (down) Relaxing the 3L Algorithm for an Accurate Implicit Polynomial Fitting Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 3066-3072
Keywords
Abstract This paper presents a novel method to increase the accuracy of linear fitting of implicit polynomials. The proposed method is based on the 3L algorithm philosophy. The novelty lies on the relaxation of the additional constraints, already imposed by the 3L algorithm. Hence, the accuracy of the final solution is increased due to the proper adjustment of the expected values in the aforementioned additional constraints. Although iterative, the proposed approach solves the fitting problem within a linear framework, which is independent of the threshold tuning. Experimental results, both in 2D and 3D, showing improvements in the accuracy of the fitting are presented. Comparisons with both state of the art algorithms and a geometric based one (non-linear fitting), which is used as a ground truth, are provided.
Address San Francisco; CA; USA; June 2010
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 1063-6919 ISBN 978-1-4244-6984-0 Medium
Area Expedition Conference CVPR
Notes ADAS Approved no
Call Number ADAS @ adas @ RoS2010a Serial 1303
Permanent link to this record
 
 
Author Marçal Rusiñol; Agnes Borras; Josep Llados
Title (down) Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images Type Journal Article
Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 31 Issue 3 Pages 188–201
Keywords Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings
Abstract This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.
Address
Corporate Author Thesis
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ RBL2010 Serial 1177
Permanent link to this record
 
 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title (down) Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions Type Conference Article
Year 2010 Publication 28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica Abbreviated Journal
Volume Issue Pages
Keywords
Abstract One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process.
Address Madrid (Spain)
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 ISBN Medium
Area 800 Expedition Conference CASEIB
Notes MV;SIAI Approved no
Call Number Admin @ si @ BSV2010 Serial 1469
Permanent link to this record
 
 
Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva
Title (down) Recursive Coarse-to-Fine Localization for fast Object Recognition Type Conference Article
Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal
Volume 6313 Issue II Pages 280–293
Keywords
Abstract Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter.
Address Crete (Greece)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-15566-6 Medium
Area Expedition Conference ECCV
Notes ISE Approved no
Call Number DAG @ dag @ PGB2010 Serial 1438
Permanent link to this record
 
 
Author David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo
Title (down) Real-time Object Segmentation using a Bag of Features Approach Type Conference Article
Year 2010 Publication 13th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal
Volume 220 Issue Pages 321–329
Keywords Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors
Abstract 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.
Address
Corporate Author Thesis
Publisher IOS Press Amsterdam, Place of Publication Editor In R.Alquezar, A.Moreno, J.Aguilar.
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 9781607506423 Medium
Area Expedition Conference CCIA
Notes ADAS Approved no
Call Number Admin @ si @ ARL2010b Serial 1417
Permanent link to this record