|   | 
Details
   web
Records
Author Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera
Title Tri-modal Person Re-identification with RGB, Depth and Thermal Features Type Conference Article
Year 2013 Publication 9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages (down) 301-307
Keywords
Abstract Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios.
Address Portland; oregon; June 2013
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 978-0-7695-4990-3 Medium
Area Expedition Conference CVPRW
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ MBM2013 Serial 2253
Permanent link to this record
 

 
Author Pau Baiget; Xavier Roca; Jordi Gonzalez
Title Autonomous Virtual Agents for Performance Evaluation of Tracking Algorithms Type Book Chapter
Year 2008 Publication Articulated Motion and Deformable Objects, 5th International Conference AMDO 2008, Abbreviated Journal
Volume 5098 Issue Pages (down) 299-308
Keywords
Abstract
Address Port d'Andratx (Mallorca)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ BRG2008 Serial 974
Permanent link to this record
 

 
Author Agata Lapedriza; Santiago Segui; David Masip; Jordi Vitria
Title A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning Type Journal
Year 2008 Publication Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications, Abbreviated Journal
Volume 11 Issue 3-4 Pages (down) 299-308
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Springer 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 OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ LSM2008 Serial 996
Permanent link to this record
 

 
Author Fadi Dornaika; Angel Sappa
Title Real Time Image Registration for Planar Structure and 3D Sensor Pose Estimation Type Book Chapter
Year 2008 Publication Stereo Vision Abbreviated Journal
Volume 18 Issue Pages (down) 299–316
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor Asim Bhatti
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ DoS2008c Serial 1057
Permanent link to this record
 

 
Author Miguel Oliveira; Angel Sappa; V. Santos
Title Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models Type Conference Article
Year 2012 Publication IEEE Intelligent Vehicles Symposium Abbreviated Journal
Volume Issue Pages (down) 299-303
Keywords
Abstract 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.
Address Alcalá de Henares
Corporate Author Thesis
Publisher IEEE Xplore Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1931-0587 ISBN 978-1-4673-2119-8 Medium
Area Expedition Conference IV
Notes ADAS Approved no
Call Number Admin @ si @ OSS2012b Serial 2021
Permanent link to this record
 

 
Author Joan Serrat; Felipe Lumbreras; Antonio Lopez
Title Cost estimation of custom hoses from STL files and CAD drawings Type Journal Article
Year 2013 Publication Computers in Industry Abbreviated Journal COMPUTIND
Volume 64 Issue 3 Pages (down) 299-309
Keywords On-line quotation; STL format; Regression; Gaussian process
Abstract We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.
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 ADAS; 600.057; 600.054; 605.203 Approved no
Call Number Admin @ si @ SLL2013; ADAS @ adas @ Serial 2161
Permanent link to this record
 

 
Author Maria Salamo; Sergio Escalera; Petia Radeva
Title Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender Type Conference Article
Year 2009 Publication 8th International Conference on Case-Based Reasoning Abbreviated Journal
Volume 5650 Issue Pages (down) 298–312
Keywords
Abstract Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches.
Address Seattle, USA
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 978-3-642-02998-1 Medium
Area Expedition Conference ICCBR
Notes HuPBA; MILAB Approved no
Call Number BCNPCL @ bcnpcl @ SER2009 Serial 1187
Permanent link to this record
 

 
Author Khalid El Asnaoui; Petia Radeva
Title Automatically Assess Day Similarity Using Visual Lifelogs Type Journal Article
Year 2020 Publication International Journal of Intelligent Systems Abbreviated Journal IJIS
Volume 29 Issue Pages (down) 298–310
Keywords
Abstract Today, we witness the appearance of many lifelogging cameras that are able to capture the life of a person wearing the camera and which produce a large number of images everyday. Automatically characterizing the experience and extracting patterns of behavior of individuals from this huge collection of unlabeled and unstructured egocentric data present major challenges and require novel and efficient algorithmic solutions. The main goal of this work is to propose a new method to automatically assess day similarity from the lifelogging images of a person. We propose a technique to measure the similarity between images based on the Swain’s distance and generalize it to detect the similarity between daily visual data. To this purpose, we apply the dynamic time warping (DTW) combined with the Swain’s distance for final day similarity estimation. For validation, we apply our technique on the Egocentric Dataset of University of Barcelona (EDUB) of 4912 daily images acquired by four persons with preliminary encouraging results.
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 MILAB; no proj Approved no
Call Number AsR2020 Serial 3409
Permanent link to this record
 

 
Author O. Fors; A. Richichi; Xavier Otazu; J. Nuñez
Title A new wavelet-based approach for the automated treatment of large sets of lunar occultation data Type Journal
Year 2008 Publication Astronomy and Astrohysics Abbreviated Journal
Volume 480 Issue Pages (down) 297–304
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
Notes CIC Approved no
Call Number CAT @ cat @ FRO2008 Serial 934
Permanent link to this record
 

 
Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title Recognition of Multi-oriented Touching Characters in Graphical Documents Type Conference Article
Year 2008 Publication Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, Abbreviated Journal
Volume 16 Issue Pages (down) 297–304
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 ICVGIP ’08
Notes DAG Approved no
Call Number DAG @ dag @ RPL2008c Serial 1080
Permanent link to this record
 

 
Author Marc Oliu; Ciprian Corneanu; Kamal Nasrollahi; Olegs Nikisins; Sergio Escalera; Yunlian Sun; Haiqing Li; Zhenan Sun; Thomas B. Moeslund; Modris Greitans
Title Improved RGB-D-T based Face Recognition Type Journal Article
Year 2016 Publication IET Biometrics Abbreviated Journal BIO
Volume 5 Issue 4 Pages (down) 297 - 303
Keywords
Abstract Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent years. At the same time a multimodal facial recognition is a promising approach. This study combines the latest successes in both directions by applying deep learning convolutional neural networks (CNN) to the multimodal RGB, depth, and thermal (RGB-D-T) based facial recognition problem outperforming previously published results. Furthermore, a late fusion of the CNN-based recognition block with various hand-crafted features (local binary patterns, histograms of oriented gradients, Haar-like rectangular features, histograms of Gabor ordinal measures) is introduced, demonstrating even better recognition performance on a benchmark RGB-D-T database. The obtained results in this study show that the classical engineered features and CNN-based features can complement each other for recognition 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 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB; Approved no
Call Number Admin @ si @ OCN2016 Serial 2854
Permanent link to this record
 

 
Author Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen
Title Top-Down Deep Appearance Attention for Action Recognition Type Conference Article
Year 2017 Publication 20th Scandinavian Conference on Image Analysis Abbreviated Journal
Volume 10269 Issue Pages (down) 297-309
Keywords Action recognition; CNNs; Feature fusion
Abstract Recognizing human actions in videos is a challenging problem in computer vision. Recently, convolutional neural network based deep features have shown promising results for action recognition. In this paper, we investigate the problem of fusing deep appearance and motion cues for action recognition. We propose a video representation which combines deep appearance and motion based local convolutional features within the bag-of-deep-features framework. Firstly, dense deep appearance and motion based local convolutional features are extracted from spatial (RGB) and temporal (flow) networks, respectively. Both visual cues are processed in parallel by constructing separate visual vocabularies for appearance and motion. A category-specific appearance map is then learned to modulate the weights of the deep motion features. The proposed representation is discriminative and binds the deep local convolutional features to their spatial locations. Experiments are performed on two challenging datasets: JHMDB dataset with 21 action classes and ACT dataset with 43 categories. The results clearly demonstrate that our approach outperforms both standard approaches of early and late feature fusion. Further, our approach is only employing action labels and without exploiting body part information, but achieves competitive performance compared to the state-of-the-art deep features based approaches.
Address Tromso; June 2017
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference SCIA
Notes LAMP; 600.109; 600.068; 600.120 Approved no
Call Number Admin @ si @ RKW2017b Serial 3039
Permanent link to this record
 

 
Author Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone
Title Towards Modelling an Attention-Based Text Localization Process Type Conference Article
Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 7887 Issue Pages (down) 296-303
Keywords text localization; visual attention; eye guidance
Abstract This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms.
Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented.
Address Madeira; Portugal; June 2013
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 978-3-642-38627-5 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number Admin @ si @ CKL2013 Serial 2291
Permanent link to this record
 

 
Author Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta
Title Diaphragm border detection in coronary X-ray angiographies: New method and applications Type Journal Article
Year 2014 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG
Volume 38 Issue 4 Pages (down) 296-305
Keywords
Abstract X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation.
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 MILAB; LAMP; 600.079 Approved no
Call Number Admin @ si @ PCR2014 Serial 2468
Permanent link to this record
 

 
Author Laura Igual; Santiago Segui; Jordi Vitria; Fernando Azpiroz; Petia Radeva
Title Eigenmotion-Based Detection of Intestinal Contractions Type Conference Article
Year 2007 Publication Computer Analysis of Images and Patterns, 12th International Conference Abbreviated Journal
Volume 4673 Issue Pages (down) 293–300
Keywords
Abstract
Address Vienna (Austria)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-540-74271-5 Medium
Area Expedition Conference CAIP
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ ISV2007a Serial 895
Permanent link to this record