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Author German Ros; Sebastian Ramos; Manuel Granados; Amir Bakhtiary; David Vazquez; Antonio Lopez
Title Vision-based Offline-Online Perception Paradigm for Autonomous Driving Type Conference Article
Year 2015 Publication (up) IEEE Winter Conference on Applications of Computer Vision Abbreviated Journal
Volume Issue Pages 231 - 238
Keywords Autonomous Driving; Scene Understanding; SLAM; Semantic Segmentation
Abstract Autonomous driving is a key factor for future mobility. Properly perceiving the environment of the vehicles is essential for a safe driving, which requires computing accurate geometric and semantic information in real-time. In this paper, we challenge state-of-the-art computer vision algorithms for building a perception system for autonomous driving. An inherent drawback in the computation of visual semantics is the trade-off between accuracy and computational cost. We propose to circumvent this problem by following an offline-online strategy. During the offline stage dense 3D semantic maps are created. In the online stage the current driving area is recognized in the maps via a re-localization process, which allows to retrieve the pre-computed accurate semantics and 3D geometry in realtime. Then, detecting the dynamic obstacles we obtain a rich understanding of the current scene. We evaluate quantitatively our proposal in the KITTI dataset and discuss the related open challenges for the computer vision community.
Address Hawaii; January 2015
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area ACDC Expedition Conference WACV
Notes ADAS; 600.076 Approved no
Call Number ADAS @ adas @ RRG2015 Serial 2499
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Author Frederic Sampedro; Sergio Escalera
Title Spatial codification of label predictions in Multi-scale Stacked Sequential Learning: A case study on multi-class medical volume segmentation Type Journal Article
Year 2015 Publication (up) IET Computer Vision Abbreviated Journal IETCV
Volume 9 Issue 3 Pages 439 - 446
Keywords
Abstract In this study, the authors propose the spatial codification of label predictions within the multi-scale stacked sequential learning (MSSL) framework, a successful learning scheme to deal with non-independent identically distributed data entries. After providing a motivation for this objective, they describe its theoretical framework based on the introduction of the blurred shape model as a smart descriptor to codify the spatial distribution of the predicted labels and define the new extended feature set for the second stacked classifier. They then particularise this scheme to be applied in volume segmentation applications. Finally, they test the implementation of the proposed framework in two medical volume segmentation datasets, obtaining significant performance improvements (with a 95% of confidence) in comparison to standard Adaboost classifier and classical MSSL approaches.
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 1751-9632 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ SaE2015 Serial 2551
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Author Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Michael Felsberg; J.Laaksonen
Title Deep semantic pyramids for human attributes and action recognition Type Conference Article
Year 2015 Publication (up) Image Analysis, Proceedings of 19th Scandinavian Conference , SCIA 2015 Abbreviated Journal
Volume 9127 Issue Pages 341-353
Keywords Action recognition; Human attributes; Semantic pyramids
Abstract Describing persons and their actions is a challenging problem due to variations in pose, scale and viewpoint in real-world images. Recently, semantic pyramids approach [1] for pose normalization has shown to provide excellent results for gender and action recognition. The performance of semantic pyramids approach relies on robust image description and is therefore limited due to the use of shallow local features. In the context of object recognition [2] and object detection [3], convolutional neural networks (CNNs) or deep features have shown to improve the performance over the conventional shallow features.
We propose deep semantic pyramids for human attributes and action recognition. The method works by constructing spatial pyramids based on CNNs of different part locations. These pyramids are then combined to obtain a single semantic representation. We validate our approach on the Berkeley and 27 Human Attributes datasets for attributes classification. For action recognition, we perform experiments on two challenging datasets: Willow and PASCAL VOC 2010. The proposed deep semantic pyramids provide a significant gain of 17.2%, 13.9%, 24.3% and 22.6% compared to the standard shallow semantic pyramids on Berkeley, 27 Human Attributes, Willow and PASCAL VOC 2010 datasets respectively. Our results also show that deep semantic pyramids outperform conventional CNNs based on the full bounding box of the person. Finally, we compare our approach with state-of-the-art methods and show a gain in performance compared to best methods in literature.
Address Denmark; Copenhagen; June 2015
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-319-19664-0 Medium
Area Expedition Conference SCIA
Notes LAMP; 600.068; 600.079;ADAS Approved no
Call Number Admin @ si @ KRW2015b Serial 2672
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Author Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez
Title Chromatic shadow detection and tracking for moving foreground segmentation Type Journal Article
Year 2015 Publication (up) Image and Vision Computing Abbreviated Journal IMAVIS
Volume 41 Issue Pages 42-53
Keywords Detecting moving objects; Chromatic shadow detection; Temporal local gradient; Spatial and Temporal brightness and angle distortions; Shadow tracking
Abstract Advanced segmentation techniques in the surveillance domain deal with shadows to avoid distortions when detecting moving objects. Most approaches for shadow detection are still typically restricted to penumbra shadows and cannot cope well with umbra shadows. Consequently, umbra shadow regions are usually detected as part of moving objects, thus a ecting the performance of the nal detection. In this paper we address the detection of both penumbra and umbra shadow regions. First, a novel bottom-up approach is presented based on gradient and colour models, which successfully discriminates between chromatic moving cast shadow regions and those regions detected as moving objects. In essence, those regions corresponding to potential shadows are detected based on edge partitioning and colour statistics. Subsequently (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for each potential shadow region for detecting the umbra shadow regions. Our second contribution re nes even further the segmentation results: a tracking-based top-down approach increases the performance of our bottom-up chromatic shadow detection algorithm by properly correcting non-detected shadows.
To do so, a combination of motion lters in a data association framework exploits the temporal consistency between objects and shadows to increase
the shadow detection rate. Experimental results exceed current state-of-the-
art in shadow accuracy for multiple well-known surveillance image databases which contain di erent shadowed materials and illumination conditions.
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; 600.078; 600.063 Approved no
Call Number Admin @ si @ HHM2015 Serial 2703
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Author Miguel Oliveira; Victor Santos; Angel Sappa
Title Multimodal Inverse Perspective Mapping Type Journal Article
Year 2015 Publication (up) Information Fusion Abbreviated Journal IF
Volume 24 Issue Pages 108–121
Keywords Inverse perspective mapping; Multimodal sensor fusion; Intelligent vehicles
Abstract Over the past years, inverse perspective mapping has been successfully applied to several problems in the field of Intelligent Transportation Systems. In brief, the method consists of mapping images to a new coordinate system where perspective effects are removed. The removal of perspective associated effects facilitates road and obstacle detection and also assists in free space estimation. There is, however, a significant limitation in the inverse perspective mapping: the presence of obstacles on the road disrupts the effectiveness of the mapping. The current paper proposes a robust solution based on the use of multimodal sensor fusion. Data from a laser range finder is fused with images from the cameras, so that the mapping is not computed in the regions where obstacles are present. As shown in the results, this considerably improves the effectiveness of the algorithm and reduces computation time when compared with the classical inverse perspective mapping. Furthermore, the proposed approach is also able to cope with several cameras with different lenses or image resolutions, as well as dynamic viewpoints.
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 ADAS; 600.055; 600.076 Approved no
Call Number Admin @ si @ OSS2015c Serial 2532
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Author Mariella Dimiccoli; Petia Radeva
Title Lifelogging in the era of outstanding digitization Type Conference Article
Year 2015 Publication (up) International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage Abbreviated Journal
Volume Issue Pages
Keywords
Abstract In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior.
Address Verliko Tarmovo; Bulgaria; September 2015
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 DiPP
Notes MILAB Approved no
Call Number Admin @ si @DiR2016 Serial 2792
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Author Miguel Oliveira; L. Seabra Lopes; G. Hyun Lim; S. Hamidreza Kasaei; Angel Sappa; A. Tom
Title Concurrent Learning of Visual Codebooks and Object Categories in Openended Domains Type Conference Article
Year 2015 Publication (up) International Conference on Intelligent Robots and Systems Abbreviated Journal
Volume Issue Pages 2488 - 2495
Keywords Visual Learning; Computer Vision; Autonomous Agents
Abstract In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are constructed from training sets created offline. This might lead to non-discriminative visual words and, as a consequence, to poor recognition performance. This paper proposes a visual object recognition system which concurrently learns in an incremental and online fashion both the visual object category representations as well as the codebook words used to encode them. The codebook is defined using Gaussian Mixture Models which are updated using new object views. The approach contains similarities with the human visual object recognition system: evidence suggests that the development of recognition capabilities occurs on multiple levels and is sustained over large periods of time. Results show that the proposed system with concurrent learning of object categories and codebooks is capable of learning more categories, requiring less examples, and with similar accuracies, when compared to the classical Bag of Words approach using offline constructed codebooks.
Address Hamburg; Germany; October 2015
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 IROS
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ OSL2015 Serial 2664
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Author G.Blasco; Simone Balocco; J.Puig; J.Sanchez-Gonzalez; W.Ricart; J.Daunis-I-Estadella; X.Molina; S.Pedraza; J.M.Fernandez-Real
Title Carotid pulse wave velocity by magnetic resonance imaging is increased in middle-aged subjects with the metabolic syndrome Type Journal Article
Year 2015 Publication (up) International Journal of Cardiovascular Imaging Abbreviated Journal ICJI
Volume 31 Issue 3 Pages 603-612
Keywords Metabolic syndrome; Arterial stiffness; Pulse wave velocity; Carotid artery; Magnetic resonance
Abstract Arterial pulse wave velocity (PWV), an independent predictor of cardiovascular disease, physiologically increases with age; however, growing evidence suggests metabolic syndrome (MetS) accelerates this increase. Magnetic resonance imaging (MRI) enables reliable noninvasive assessment of arterial stiffness by measuring arterial PWV in specific vascular segments. We investigated the association between the presence of MetS and its components with carotid PWV (cPWV) in asymptomatic subjects without diabetes. We assessed cPWV by MRI in 61 individuals (mean age, 55.3 ± 14.1 years; median age, 55 years): 30 with MetS and 31 controls with similar age, sex, body mass index, and LDL-cholesterol levels. The study population was dichotomized by the median age. To remove the physiological association between PWV and age, unpaired t tests and multiple regression analyses were performed using the residuals of the regression between PWV and age. cPWV was higher in middle-aged subjects with MetS than in those without (p = 0.001), but no differences were found in elder subjects (p = 0.313). cPWV was associated with diastolic blood pressure (r = 0.276, p = 0.033) and waist circumference (r = 0.268, p = 0.038). The presence of MetS was associated with increased cPWV regardless of age, sex, blood pressure, and waist (p = 0.007). The MetS components contributing independently to an increased cPWV were hypertension (p = 0.018) and hypertriglyceridemia (p = 0.002). The presence of MetS is associated with an increased cPWV in middle-aged subjects. In particular, hypertension and hypertriglyceridemia may contribute to early progression of carotid stiffness.
Address
Corporate Author Thesis
Publisher Springer Netherlands Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1569-5794 ISBN Medium
Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ BBP2015 Serial 2670
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Author Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil
Title Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy Type Journal Article
Year 2015 Publication (up) International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR
Volume 10 Issue 6 Pages 935-945
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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 IAM; MV; 600.075 Approved no
Call Number Admin @ si @ SBS2015a Serial 2611
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Author Wenjuan Gong; W.Zhang; Jordi Gonzalez; Y.Ren; Z.Li
Title Enhanced Asymmetric Bilinear Model for Face Recognition Type Journal Article
Year 2015 Publication (up) International Journal of Distributed Sensor Networks Abbreviated Journal IJDSN
Volume Issue Pages Article ID 218514
Keywords
Abstract Bilinear models have been successfully applied to separate two factors, for example, pose variances and different identities in face recognition problems. Asymmetric model is a type of bilinear model which models a system in the most concise way. But seldom there are works exploring the applications of asymmetric bilinear model on face recognition problem with illumination changes. In this work, we propose enhanced asymmetric model for illumination-robust face recognition. Instead of initializing the factor probabilities randomly, we initialize them with nearest neighbor method and optimize them for the test data. Above that, we update the factor model to be identified. We validate the proposed method on a designed data sample and extended Yale B dataset. The experiment results show that the enhanced asymmetric models give promising results and good recognition accuracies.
Address
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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; 600.063; 600.078 Approved no
Call Number Admin @ si @ GZG2015 Serial 2592
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Author Aura Hernandez-Sabate; Meritxell Joanpere; Nuria Gorgorio; Lluis Albarracin
Title Mathematics learning opportunities when playing a Tower Defense Game Type Journal
Year 2015 Publication (up) International Journal of Serious Games Abbreviated Journal IJSG
Volume 2 Issue 4 Pages 57-71
Keywords Tower Defense game; learning opportunities; mathematics; problem solving; game design
Abstract A qualitative research study is presented herein with the purpose of identifying mathematics learning opportunities in students between 10 and 12 years old while playing a commercial version of a Tower Defense game. These learning opportunities are understood as mathematicisable moments of the game and involve the establishment of relationships between the game and mathematical problem solving. Based on the analysis of these mathematicisable moments, we conclude that the game can promote problem-solving processes and learning opportunities that can be associated with different mathematical contents that appears in mathematics curricula, thought it seems that teacher or new game elements might be needed to facilitate the processes.
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 ADAS; 600.076 Approved no
Call Number Admin @ si @ HJG2015 Serial 2730
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Author Lluis Pere de las Heras; Oriol Ramos Terrades; Sergi Robles; Gemma Sanchez
Title CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool Type Journal Article
Year 2015 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 1 Pages 15-30
Keywords
Abstract Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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; ADAS; 600.061; 600.076; 600.077 Approved no
Call Number Admin @ si @ HRR2015 Serial 2567
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Author Christophe Rigaud; Clement Guerin; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier
Title Knowledge-driven understanding of images in comic books Type Journal Article
Year 2015 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 3 Pages 199-221
Keywords Document Understanding; comics analysis; expert system
Abstract Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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; 600.056; 600.077 Approved no
Call Number RGK2015 Serial 2595
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Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados
Title A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting Type Journal Article
Year 2015 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 18 Issue 3 Pages 223-234
Keywords Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation
Abstract The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 Approved no
Call Number Admin @ si @ ART2015 Serial 2679
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Author Dan Norton; Fernando Vilariño; Onur Ferhat
Title Memory Field – Creative Engagement in Digital Collections Type Conference Article
Year 2015 Publication (up) Internet Librarian International Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract “Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields).
Address London; UK; October 2015
Corporate Author Thesis
Publisher Place of Publication Editor
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ILI
Notes MV;SIAI Approved no
Call Number Admin @ si @NVF2015 Serial 2796
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