Publicacions CVC -- Query Results

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	Login Quick Search: Field: contains: ...
	106–120 of 170 records found matching your query (RSS \| history):

Search & Display Options

Select All Deselect All

<< 1 2 3 4 5 6 7 8 9 10 >> [11–12]

List View

Citations

Details

	Records
	Author	Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva
	Title	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	Mario Rojas; David Masip; A. Todorov; Jordi Vitria
	Title	Automatic Point-based Facial Trait Judgments Evaluation			Type	Conference Article
	Year	2010	Publication	23rd IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	2715–2720
	Keywords
	Abstract	Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits.
	Address	San Francisco CA, USA
	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	OR;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RMT2010			Serial	1282
Permanent link to this record



	Author	Marta Teres; Eduard Vazquez
	Title	Museums, spaces and museographical resources. Current state and proposals for a multidisciplinary framework to open new perspectives			Type	Conference Article
	Year	2010	Publication	Proceedings of The CREATE 2010 Conference	Abbreviated Journal
	Volume		Issue		Pages	319–323
	Keywords
	Abstract	Two of the main aims of a museum are to communicate its heritage and to make enjoy its visitors. This communication can be done through the pieces itself and the museographical resources but also through the building, the interior design, the light and the colour. Art museums, in opposition with other museums, lack on the application of these additional resources. Such a work necessarily requires a multidisciplinary point of view for a holistic vision of all what a museum implies and to use all its potential as a tool of knowledge and culture for all the visitors.
	Address	Gjovik, Norway
	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	CREATE
	Notes				Approved	no
	Call Number	Admin @ si @ TeV2010			Serial	1298
Permanent link to this record



	Author	Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas
	Title	Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems			Type	Journal Article
	Year	2010	Publication	International Journal on Document Analysis and Recognition	Abbreviated Journal	IJDAR
	Volume	13	Issue	3	Pages	187-207
	Keywords
	Abstract	This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.
	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			Approved	no
	Call Number	DAG @ dag @ DVP2010			Serial	1289
Permanent link to this record



	Author	Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
	Title	A Performance Characterization Algorithm for Symbol Localization			Type	Book Chapter
	Year	2010	Publication	Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers	Abbreviated Journal
	Volume	6020	Issue		Pages	260–271
	Keywords
	Abstract	In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
	Address
	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	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DRV2010			Serial	2406
Permanent link to this record



	Author	Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil
	Title	A quantitative and statistically robust method for the determination of xylem conduit spatial distribution			Type	Journal Article
	Year	2010	Publication	American Journal of Botany	Abbreviated Journal	AJB
	Volume	97	Issue	8	Pages	1247-1259
	Keywords	Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network
	Abstract	Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns.
	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	IAM;			Approved	no
	Call Number	IAM @ iam @ MMG2010			Serial	1623
Permanent link to this record



	Author	Michal Drozdzal; Laura Igual; Jordi Vitria; Petia Radeva; Carolina Malagelada; Fernando Azpiroz
	Title	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
Permanent link to this record



	Author	Michal Drozdzal; Laura Igual; Petia Radeva; Jordi Vitria; Carolina Malagelada; Fernando Azpiroz
	Title	Aligning Endoluminal Scene Sequences in Wireless Capsule Endoscopy			Type	Conference Article
	Year	2010	Publication	IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis	Abbreviated Journal
	Volume		Issue		Pages	117–124
	Keywords
	Abstract	Intestinal motility analysis is an important examination in detection of various intestinal malfunctions. One of the big challenges of automatic motility analysis is how to compare sequence of images and extract dynamic paterns taking into account the high deformability of the intestine wall as well as the capsule motion. From clinical point of view the ability to align endoluminal scene sequences will help to find regions of similar intestinal activity and in this way will provide a valuable information on intestinal motility problems. This work, for first time, addresses the problem of aligning endoluminal sequences taking into account motion and structure of the intestine. To describe motility in the sequence, we propose different descriptors based on the Sift Flow algorithm, namely: (1) Histograms of Sift Flow Directions to describe the flow course, (2) Sift Descriptors to represent image intestine structure and (3) Sift Flow Magnitude to quantify intestine deformation. We show that the merge of all three descriptors provides robust information on sequence description in terms of motility. Moreover, we develop a novel methodology to rank the intestinal sequences based on the expert feedback about relevance of the results. The experimental results show that the selected descriptors are useful in the alignment and similarity description and the proposed method allows the analysis of the WCE.
	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	MMBIA
	Notes	OR;MILAB;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ DIR2010			Serial	1316
Permanent link to this record



	Author	Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva
	Title	Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications			Type	Conference Article
	Year	2010	Publication	European Conference on Machine Learning	Abbreviated Journal
	Volume	I	Issue		Pages	119-128
	Keywords
	Abstract
	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	ECML
	Notes	MILAB; OR;HUPBA;MV			Approved	no
	Call Number	Admin @ si @ BEB2010			Serial	1775
Permanent link to this record



	Author	Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera
	Title	Compact Evolutive Design of Error-Correcting Output Codes			Type	Conference Article
	Year	2010	Publication	Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases	Abbreviated Journal
	Volume		Issue		Pages	119-128
	Keywords	Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization
	Abstract	The classication of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classiers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classiers. Evolutionary computation is used for tuning the parameters of the classiers and looking for the best Minimal ECOC code conguration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
	Address	Barcelona (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	SUEMA
	Notes	OR;MILAB;HUPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ BBP2010			Serial	1363
Permanent link to this record



	Author	Miguel Reyes; Jordi Vitria; Petia Radeva; Sergio Escalera
	Title	Real-time Activity Monitoring of Inpatients			Type	Conference Article
	Year	2010	Publication	Medical Image Computing in Catalunya: Graduate Student Workshop	Abbreviated Journal
	Volume		Issue		Pages	35–36
	Keywords
	Abstract	In this paper, we present the development of an application capable of monitoring a set of patient vital signs in real time. The application has been designed to support the medical staff of a hospital. Preliminary results show the suitability of the system to prevent the injury produced by the agitation of the patients.
	Address	Girona
	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;HUPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ RVR2010			Serial	1477
Permanent link to this record



	Author	Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez
	Title	Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences			Type	Journal Article
	Year	2010	Publication	EURASIP Journal on Advances in Signal Processing	Abbreviated Journal	EURASIPJ
	Volume		Issue		Pages
	Keywords
	Abstract	Article ID 507247 A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
	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 @ MRR2010			Serial	1208
Permanent link to this record



	Author	Miquel Ferrer; Ernest Valveny; F. Serratosa; K. Riesen; Horst Bunke
	Title	Generalized Median Graph Computation by Means of Graph Embedding in Vector Spaces			Type	Journal Article
	Year	2010	Publication	Pattern Recognition	Abbreviated Journal	PR
	Volume	43	Issue	4	Pages	1642–1655
	Keywords	Graph matching; Weighted mean of graphs; Median graph; Graph embedding; Vector spaces
	Abstract	The median graph has been presented as a useful tool to represent a set of graphs. Nevertheless its computation is very complex and the existing algorithms are restricted to use limited amount of data. In this paper we propose a new approach for the computation of the median graph based on graph embedding. Graphs are embedded into a vector space and the median is computed in the vector domain. We have designed a procedure based on the weighted mean of a pair of graphs to go from the vector domain back to the graph domain in order to obtain a final approximation of the median graph. Experiments on three different databases containing large graphs show that we succeed to compute good approximations of the median graph. We have also applied the median graph to perform some basic classification tasks achieving reasonable good results. These experiments on real data open the door to the application of the median graph to a number of more complex machine learning algorithms where a representative of a set of graphs is needed.
	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 @ FVS2010			Serial	1294
Permanent link to this record



	Author	Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey
	Title	Automatic segmentation and inpainting of specular highlights for endoscopic imaging			Type	Journal Article
	Year	2010	Publication	EURASIP Journal on Image and Video Processing	Abbreviated Journal	EURASIP JIVP
	Volume	2010	Issue	9	Pages
	Keywords
	Abstract
	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	800	Expedition		Conference
	Notes	MV			Approved	no
	Call Number	fernando @ fernando @			Serial	2423
Permanent link to this record



	Author	Mohammad Rouhani; Angel Sappa
	Title	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