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Author H. Emrah Tasli; Jan van Gemert; Theo Gevers
Title Spot the differences: from a photograph burst to the single best picture Type Conference Article
Year 2013 Publication 21ST ACM International Conference on Multimedia Abbreviated Journal
Volume Issue Pages 729-732
Keywords
Abstract With the rise of the digital camera, people nowadays typically take several near-identical photos of the same scene to maximize the chances of a good shot. This paper proposes a user-friendly tool for exploring a personal photo gallery for selecting or even creating the best shot of a scene between its multiple alternatives. This functionality is realized through a graphical user interface where the best viewpoint can be selected from a generated panorama of the scene. Once the viewpoint is selected, the user is able to go explore possible alternatives coming from the other images. Using this tool, one can explore a photo gallery efficiently. Moreover, additional compositions from other images are also possible. With such additional compositions, one can go from a burst of photographs to the single best one. Even funny compositions of images, where you can duplicate a person in the same image, are possible with our proposed tool.
Address Barcelona
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 (up) ACM-MM
Notes ALTRES;ISE Approved no
Call Number TGG2013 Serial 2368
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Author Sezer Karaoglu; Jan van Gemert; Theo Gevers
Title Con-text: text detection using background connectivity for fine-grained object classification Type Conference Article
Year 2013 Publication 21ST ACM International Conference on Multimedia Abbreviated Journal
Volume Issue Pages 757-760
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 (up) ACM-MM
Notes ALTRES;ISE Approved no
Call Number Admin @ si @ KGG2013 Serial 2369
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Author Yaxing Wang; Abel Gonzalez-Garcia; Joost Van de Weijer; Luis Herranz
Title SDIT: Scalable and Diverse Cross-domain Image Translation Type Conference Article
Year 2019 Publication 27th ACM International Conference on Multimedia Abbreviated Journal
Volume Issue Pages 1267–1276
Keywords
Abstract Recently, image-to-image translation research has witnessed remarkable progress. Although current approaches successfully generate diverse outputs or perform scalable image transfer, these properties have not been combined into a single method. To address this limitation, we propose SDIT: Scalable and Diverse image-to-image translation. These properties are combined into a single generator. The diversity is determined by a latent variable which is randomly sampled from a normal distribution. The scalability is obtained by conditioning the network on the domain attributes. Additionally, we also exploit an attention mechanism that permits the generator to focus on the domain-specific attribute. We empirically demonstrate the performance of the proposed method on face mapping and other datasets beyond faces.
Address Nice; Francia; October 2019
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 (up) ACM-MM
Notes LAMP; 600.106; 600.109; 600.141; 600.120 Approved no
Call Number Admin @ si @ WGW2019 Serial 3363
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Author Silvio Giancola; Anthony Cioppa; Adrien Deliege; Floriane Magera; Vladimir Somers; Le Kang; Xin Zhou; Olivier Barnich; Christophe De Vleeschouwer; Alexandre Alahi; Bernard Ghanem; Marc Van Droogenbroeck; Abdulrahman Darwish; Adrien Maglo; Albert Clapes; Andreas Luyts; Andrei Boiarov; Artur Xarles; Astrid Orcesi; Avijit Shah; Baoyu Fan; Bharath Comandur; Chen Chen; Chen Zhang; Chen Zhao; Chengzhi Lin; Cheuk-Yiu Chan; Chun Chuen Hui; Dengjie Li; Fan Yang; Fan Liang; Fang Da; Feng Yan; Fufu Yu; Guanshuo Wang; H. Anthony Chan; He Zhu; Hongwei Kan; Jiaming Chu; Jianming Hu; Jianyang Gu; Jin Chen; Joao V. B. Soares; Jonas Theiner; Jorge De Corte; Jose Henrique Brito; Jun Zhang; Junjie Li; Junwei Liang; Leqi Shen; Lin Ma; Lingchi Chen; Miguel Santos Marques; Mike Azatov; Nikita Kasatkin; Ning Wang; Qiong Jia; Quoc Cuong Pham; Ralph Ewerth; Ran Song; Rengang Li; Rikke Gade; Ruben Debien; Runze Zhang; Sangrok Lee; Sergio Escalera; Shan Jiang; Shigeyuki Odashima; Shimin Chen; Shoichi Masui; Shouhong Ding; Sin-wai Chan; Siyu Chen; Tallal El-Shabrawy; Tao He; Thomas B. Moeslund; Wan-Chi Siu; Wei Zhang; Wei Li; Xiangwei Wang; Xiao Tan; Xiaochuan Li; Xiaolin Wei; Xiaoqing Ye; Xing Liu; Xinying Wang; Yandong Guo; Yaqian Zhao; Yi Yu; Yingying Li; Yue He; Yujie Zhong; Zhenhua Guo; Zhiheng Li
Title SoccerNet 2022 Challenges Results Type Conference Article
Year 2022 Publication 5th International ACM Workshop on Multimedia Content Analysis in Sports Abbreviated Journal
Volume Issue Pages 75-86
Keywords
Abstract The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks: (1) action spotting, focusing on retrieving action timestamps in long untrimmed videos, (2) replay grounding, focusing on retrieving the live moment of an action shown in a replay, (3) pitch localization, focusing on detecting line and goal part elements, (4) camera calibration, dedicated to retrieving the intrinsic and extrinsic camera parameters, (5) player re-identification, focusing on retrieving the same players across multiple views, and (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams. Compared to last year's challenges, tasks (1-2) had their evaluation metrics redefined to consider tighter temporal accuracies, and tasks (3-6) were novel, including their underlying data and annotations. More information on the tasks, challenges and leaderboards are available on this https URL. Baselines and development kits are available on this https URL.
Address Lisboa; Portugal; October 2022
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 (up) ACMW
Notes HUPBA; no menciona Approved no
Call Number Admin @ si @ GCD2022 Serial 3801
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Author Aniol Lidon; Marc Bolaños; Mariella Dimiccoli; Petia Radeva; Maite Garolera; Xavier Giro
Title Semantic Summarization of Egocentric Photo-Stream Events Type Conference Article
Year 2017 Publication 2nd Workshop on Lifelogging Tools and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address San Francisco; USA; October 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 978-1-4503-5503-2 Medium
Area Expedition Conference (up) ACMW (LTA)
Notes MILAB; no proj Approved no
Call Number Admin @ si @ LBD2017 Serial 3024
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Author Pierdomenico Fiadino; Victor Ponce; Juan Antonio Torrero-Gonzalez; Marc Torrent-Moreno
Title Call Detail Records for Human Mobility Studies: Taking Stock of the Situation in the “Always Connected Era" Type Conference Article
Year 2017 Publication Workshop on Big Data Analytics and Machine Learning for Data Communication Networks Abbreviated Journal
Volume Issue Pages 43-48
Keywords mobile networks; call detail records; human mobility
Abstract The exploitation of cellular network data for studying human mobility has been a popular research topic in the last decade. Indeed, mobile terminals could be considered ubiquitous sensors that allow the observation of human movements on large scale without the need of relying on non-scalable techniques, such as surveys, or dedicated and expensive monitoring infrastructures. In particular, Call Detail Records (CDRs), collected by operators for billing purposes,
have been extensively employed due to their rather large availability, compared to other types of cellular data (e.g., signaling). Despite the interest aroused around this topic, the research community has generally agreed about the scarcity of information provided by CDRs: the position of mobile terminals is logged when some kind of activity (calls, SMS, data connections) occurs, which translates in a picture of mobility somehow biased by the activity degree of users.
By studying two datasets collected by a Nation-wide operator in 2014 and 2016, we show that the situation has drastically changed in terms of data volume and quality. The increase of flat data plans and the higher penetration of “
always connected” terminals have driven up the number of recorded CDRs, providing higher temporal accuracy for users’ locations.
Address UCLA; USA; August 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 978-1-4503-5054-9 Medium
Area Expedition Conference (up) ACMW (SIGCOMM)
Notes HuPBA; no menciona Approved no
Call Number Admin @ si @ FPT2017 Serial 2980
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Author Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; Isis Ara
Title Utilidad de la visión por computador para la localización de pólipos pequeños y planos Type Conference Article
Year 2016 Publication XIX Reunión Nacional de la Asociación Española de Gastroenterología, Gastroenterology Hepatology Abbreviated Journal
Volume 39 Issue 2 Pages 94
Keywords
Abstract
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 Expedition Conference (up) AEGASTRO
Notes MV; IAM; 600.097;SIAI Approved no
Call Number Admin @ si @FBR2016 Serial 2779
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Author Gemma Sanchez; Josep Llados; Enric Marti
Title Segmentation and analysis of linial texture in plans Type Conference Article
Year 1997 Publication Intelligence Artificielle et Complexité. Abbreviated Journal
Volume Issue Pages
Keywords Structural Texture, Voronoi, Hierarchical Clustering, String Matching.
Abstract The problem of texture segmentation and interpretation is one of the main concerns in the field of document analysis. Graphical documents often contain areas characterized by a structural texture whose recognition allows both the document understanding, and its storage in a more compact way. In this work, we focus on structural linial textures of regular repetition contained in plan documents. Starting from an atributed graph which represents the vectorized input image, we develop a method to segment textured areas and recognize their placement rules. We wish to emphasize that the searched textures do not follow a predefined pattern. Minimal closed loops of the input graph are computed, and then hierarchically clustered. In this hierarchical clustering, a distance function between two closed loops is defined in terms of their areas difference and boundary resemblance computed by a string matching procedure. Finally it is noted that, when the texture consists of isolated primitive elements, the same method can be used after computing a Voronoi Tesselation of the input graph.
Address Paris, France
Corporate Author Thesis
Publisher Place of Publication Paris Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference (up) AERFAI
Notes DAG;IAM; Approved no
Call Number IAM @ iam @ SLM1997 Serial 1649
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Author Carles Fernandez; Pau Baiget; Xavier Roca; Jordi Gonzalez
Title Semantic Annotation of Complex Human Scenes for Multimedia Surveillance Type Conference Article
Year 2007 Publication AI* Artificial Intelligence and Human–Oriented Computing. 10th Congress of the Italian Association for Artificial Intelligence, Abbreviated Journal
Volume 4733 Issue Pages 698–709
Keywords
Abstract
Address Roma (Italy)
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 (up) AI
Notes ISE Approved no
Call Number ISE @ ise @ FBR2007a Serial 920
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Efficient pairwise classification using Local Cross Off strategy Type Conference Article
Year 2012 Publication 25th Canadian Conference on Artificial Intelligence Abbreviated Journal
Volume 7310 Issue Pages 25-36
Keywords
Abstract The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presented and evaluated in this paper. The proposed LCO system takes advantage of nearest neighbor classification algorithm because of its simplicity and speed, as well as the strength of other two powerful binary classifiers to discriminate between two classes. This paper provides a set of experimental results on 20 datasets using two base learners: Neural Networks and Support Vector Machines. The results show that the proposed technique not only achieves better classification accuracy, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes.
Address Toronto, Ontario
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 0302-9743 ISBN 978-3-642-30352-4 Medium
Area Expedition Conference (up) AI
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2012c Serial 2044
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers Type Conference Article
Year 2013 Publication 26th Canadian Conference on Artificial Intelligence Abbreviated Journal
Volume 7884 Issue Pages 1-12
Keywords Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature
Abstract Best paper award
The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of three classifiers, each trained on different feature sets. Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features is fed into an individual classifier. In order to reduce recognition error, a powerful combination strategy based on the Dempster-Shafer theory is utilized to fuse the three classifiers trained on different sources of information. This combination strategy can effectively make use of diversity of base learners generated with different set of features. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing significant performance improvements of the proposed methodology.
Address Canada; May 2013
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 0302-9743 ISBN 978-3-642-38456-1 Medium
Area Expedition Conference (up) AI
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2013b Serial 2249
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Action Recognition by Pairwise Proximity Function Support Vector Machines with Dynamic Time Warping Kernels Type Conference Article
Year 2016 Publication 29th Canadian Conference on Artificial Intelligence Abbreviated Journal
Volume 9673 Issue Pages 3-14
Keywords
Abstract In the context of human action recognition using skeleton data, the 3D trajectories of joint points may be considered as multi-dimensional time series. The traditional recognition technique in the literature is based on time series dis(similarity) measures (such as Dynamic Time Warping). For these general dis(similarity) measures, k-nearest neighbor algorithms are a natural choice. However, k-NN classifiers are known to be sensitive to noise and outliers. In this paper, a new class of Support Vector Machine that is applicable to trajectory classification, such as action recognition, is developed by incorporating an efficient time-series distances measure into the kernel function. More specifically, the derivative of Dynamic Time Warping (DTW) distance measure is employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite (PSD) kernels in the SVM formulation. The recognition results of the proposed technique on two action recognition datasets demonstrates the ourperformance of our methodology compared to the state-of-the-art methods. Remarkably, we obtained 89 % accuracy on the well-known MSRAction3D dataset using only 3D trajectories of body joints obtained by Kinect
Address Victoria; Canada; May 2016
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 ISBN Medium
Area Expedition Conference (up) AI
Notes HuPBA;MILAB; Approved no
Call Number Admin @ si @ BGE2016b Serial 2770
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
Title Error Correcting Output Codes for multiclass classification: Application to two image vision problems Type Conference Article
Year 2012 Publication 16th symposium on Artificial Intelligence & Signal Processing Abbreviated Journal
Volume Issue Pages 508-513
Keywords
Abstract Error-correcting output codes (ECOC) represents a powerful framework to deal with multiclass classification problems based on combining binary classifiers. The key factor affecting the performance of ECOC methods is the independence of binary classifiers, without which the ECOC method would be ineffective. In spite of its ability on classification of problems with relatively large number of classes, it has been applied in few real world problems. In this paper, we investigate the behavior of the ECOC approach on two image vision problems: logo recognition and shape classification using Decision Tree and AdaBoost as the base learners. The results show that the ECOC method can be used to improve the classification performance in comparison with the classical multiclass approaches.
Address Shiraz, Iran
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 ISBN 978-1-4673-1478-7 Medium
Area Expedition Conference (up) AISP
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ BGE2012b Serial 2042
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Author Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo
Title Feature Selection Based on Reinforcement Learning for Object Recognition Type Conference Article
Year 2012 Publication Adaptive Learning Agents Workshop Abbreviated Journal
Volume Issue Pages 33-39
Keywords
Abstract
Address Valencia
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 (up) ALA
Notes ADAS; RV Approved no
Call Number Admin @ si @ PSL2012 Serial 2018
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Author Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas
Title Opinion Mining on Educational Resources at the Open University of Catalonia Type Conference Article
Year 2013 Publication 3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems Abbreviated Journal
Volume Issue Pages 385 - 390
Keywords
Abstract In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question.
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 978-0-7695-4992-7 Medium
Area Expedition Conference (up) ALICE
Notes OR;MV Approved no
Call Number GCV2013 Serial 2268
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