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Author Carles Sanchez; Antonio Esteban Lansaque; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil
Title (down) Towards a Videobronchoscopy Localization System from Airway Centre Tracking Type Conference Article
Year 2017 Publication 12th International Conference on Computer Vision Theory and Applications Abbreviated Journal
Volume Issue Pages 352-359
Keywords Video-bronchoscopy; Lung cancer diagnosis; Airway lumen detection; Region tracking; Guided bronchoscopy navigation
Abstract Bronchoscopists use fluoroscopy to guide flexible bronchoscopy to the lesion to be biopsied without any kind of incision. Being fluoroscopy an imaging technique based on X-rays, the risk of developmental problems and cancer is increased in those subjects exposed to its application, so minimizing radiation is crucial. Alternative guiding systems such as electromagnetic navigation require specific equipment, increase the cost of the clinical procedure and still require fluoroscopy. In this paper we propose an image based guiding system based on the extraction of airway centres from intra-operative videos. Such anatomical landmarks are matched to the airway centreline extracted from a pre-planned CT to indicate the best path to the nodule. We present a
feasibility study of our navigation system using simulated bronchoscopic videos and a multi-expert validation of landmarks extraction in 3 intra-operative ultrathin explorations.
Address Porto; Portugal; February 2017
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 VISAPP
Notes IAM; 600.096; 600.075; 600.145 Approved no
Call Number Admin @ si @ SEB2017 Serial 2943
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Author C. Alejandro Parraga; Robert Benavente; Maria Vanrell
Title (down) Towards a general model of colour categorization which considers context Type Journal Article
Year 2010 Publication Perception. ECVP Abstract Supplement Abbreviated Journal PER
Volume 39 Issue Pages 86
Keywords
Abstract In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we
completed our parametric fuzzy-sets model of colour naming space.
Address
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Notes CIC Approved no
Call Number CAT @ cat @ PBV2010b Serial 1326
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Author Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen
Title (down) 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 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
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Author X. Binefa; Jordi Vitria; Juan J. Villanueva
Title (down) Three dimensional inspection of integrated circuits: a depth from focus approach. Type Conference Article
Year 1992 Publication SPIE/IS&T Symposium on Electronic Imaging (Conference on Machine Vision in Microelectronics Manufacturing) Abbreviated Journal
Volume Issue Pages
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Address
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ BVV1992a Serial 250
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Author Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño
Title (down) Texture-based Polyp Detection in Colonoscopy Type Conference Article
Year 2009 Publication Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN Abbreviated Journal
Volume Issue Pages
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Abstract
Address
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Series Editor Series Title Abbreviated Series Title
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Area 800 Expedition Conference
Notes MV;SIAI Approved no
Call Number fernando @ fernando @ Serial 2428
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Author Craig Von Land; Ricardo Toledo; Juan J. Villanueva
Title (down) TeleRegions: Application of Telematics in Cardiac Care. Type Conference Article
Year 1997 Publication Computers In Cardiology Abbreviated Journal
Volume Issue Pages 195-198
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Abstract
Address Lund, Sweden, 1997
Corporate Author Thesis
Publisher Place of Publication Editor
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Area Expedition Conference
Notes ADAS Approved no
Call Number ISE @ ise @ VTV1997 Serial 64
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Author N. Pares; J.R. Serra
Title (down) Tailleur: El problema del sastre. Type Conference Article
Year 1992 Publication V Simposium Nacional de Reconocimiento de Formas y Analisis de Imagenes. Abbreviated Journal
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Abstract
Address
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Notes Approved no
Call Number Admin @ si @ PaS1992 Serial 252
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Author Josep Llados; Ernest Valveny; Enric Marti
Title (down) Symbol Recognition in Document Image Analysis: Methods and Challenges Type Book Chapter
Year 2000 Publication Recent Research Developments in Pattern Recognition, Transworld Research Network, Abbreviated Journal
Volume 1 Issue Pages 151–178.
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Address
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Series Editor Series Title Abbreviated Series Title
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ISSN ISBN 81-86846-61-1 Medium
Area Expedition Conference
Notes DAG;IAM Approved no
Call Number IAM @ iam @ LVM2000 Serial 1575
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Author Josep Llados; Enric Marti; Juan J.Villanueva
Title (down) Symbol recognition by error-tolerant subgraph matching between region adjacency graphs Type Journal Article
Year 2001 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal
Volume 23 Issue 10 Pages 1137-1143
Keywords
Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
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Notes DAG;IAM;ISE; Approved no
Call Number IAM @ iam @ LMV2001 Serial 1581
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Author Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Hugo Jair Escalante; Zhen Lei
Title (down) Surveillance Face Presentation Attack Detection Challenge Type Conference Article
Year 2023 Publication Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops Abbreviated Journal
Volume Issue Pages 6360-6370
Keywords
Abstract Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios. Specifically, compared with FAS in traditional scenes such as phone unlocking, face payment, and self-service security inspection, FAS in long-distance such as station squares, parks, and self-service supermarkets are equally important, but it has not been sufficiently explored yet. In order to fill this gap in the FAS community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask). SuHiFiMask contains 10,195 videos from 101 subjects of different age groups, which are collected by 7 mainstream surveillance cameras. Based on this dataset and protocol-3 for evaluating the robustness of the algorithm under quality changes, we organized a face presentation attack detection challenge in surveillance scenarios. It attracted 180 teams for the development phase with a total of 37 teams qualifying for the final round. The organization team re-verified and re-ran the submitted code and used the results as the final ranking. In this paper, we present an overview of the challenge, including an introduction to the dataset used, the definition of the protocol, the evaluation metrics, and the announcement of the competition results. Finally, we present the top-ranked algorithms and the research ideas provided by the competition for attack detection in long-range surveillance scenarios.
Address Vancouver; Canada; June 2023
Corporate Author Thesis
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CVPRW
Notes HuPBA Approved no
Call Number Admin @ si @ FLW2023 Serial 3917
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Author Anna Salvatella; Maria Vanrell; Ramon Baldrich
Title (down) Subtexture Components for Texture Description Type Conference Article
Year 2003 Publication 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 Abbreviated Journal
Volume 2652 Issue Pages 884-892
Keywords
Abstract
Address Springer-Verlag
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 IbPRIA
Notes CIC Approved no
Call Number CAT @ cat @ SVR2003 Serial 421
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Author Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi
Title (down) Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars Type Journal Article
Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM
Volume 150 Issue A Pages 147-154
Keywords document image analysis; stochastic context-free grammars; text classi cation features
Abstract In this paper we de ne a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classi cation features are used to perform an initial classi cation of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models
and the results showed that the proposed grammatical model outperformed
the other methods. Furthermore, grammars also provide the document structure
along with its segmentation.
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Notes DAG; 601.158; 600.077; 600.061 Approved no
Call Number Admin @ si @ ACS2015 Serial 2531
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Author Manuel Graña; Bogdan Raducanu
Title (down) Special Issue on Bioinspired and knowledge based techniques and applications Type Journal Article
Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM
Volume Issue Pages 1-3
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Abstract
Address
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Notes LAMP; Approved no
Call Number Admin @ si @ GrR2015 Serial 2598
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Author Daniel Hernandez; Lukas Schneider; Antonio Espinosa; David Vazquez; Antonio Lopez; Uwe Franke; Marc Pollefeys; Juan C. Moure
Title (down) Slanted Stixels: Representing San Francisco's Steepest Streets Type Conference Article
Year 2017 Publication 28th British Machine Vision Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive geometric assumptions for Stixels by introducing a novel depth model to account for non-flat roads and slanted objects. Both semantic and depth cues are used jointly to infer the scene representation in a sound global energy minimization formulation. Furthermore, a novel approximation scheme is introduced that uses an extremely efficient over-segmentation. In doing so, the computational complexity of the Stixel inference algorithm is reduced significantly, achieving real-time computation capabilities with only a slight drop in accuracy. We evaluate the proposed approach in terms of semantic and geometric accuracy as well as run-time on four publicly available benchmark datasets. Our approach maintains accuracy on flat road scene datasets while improving substantially on a novel non-flat road dataset.
Address London; uk; September 2017
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ISSN ISBN Medium
Area Expedition Conference BMVC
Notes ADAS; 600.118 Approved no
Call Number ADAS @ adas @ HSE2017a Serial 2945
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Author David Guillamet; Jordi Vitria
Title (down) Skin segmentation using non linear principal component analysis. Type Conference Article
Year 1999 Publication Proc. 2nd Catalan Congress on Artificial Intelligence (CCIA’99) Abbreviated Journal
Volume Issue Pages 224-231
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Abstract
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 CCIA
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ GuV1999b Serial 48
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