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Author Marc Bolaños; Maite Garolera; Petia Radeva edit  doi
isbn  openurl
  Title Object Discovery using CNN Features in Egocentric Videos Type Conference Article
  Year 2015 Publication Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 Abbreviated Journal  
  Volume 9117 Issue (down) Pages 67-74  
  Keywords Object discovery; Egocentric videos; Lifelogging; CNN  
  Abstract Lifelogging devices based on photo/video are spreading faster everyday. This growth can represent great benefits to develop methods for extraction of meaningful information about the user wearing the device and his/her environment. In this paper, we propose a semi-supervised strategy for easily discovering objects relevant to the person wearing a first-person camera. The egocentric video sequence acquired by the camera, uses both the appearance extracted by means of a deep convolutional neural network and an object refill methodology that allow to discover objects even in case of small amount of object appearance in the collection of images. We validate our method on a sequence of 1000 egocentric daily images and obtain results with an F-measure of 0.5, 0.17 better than the state of the art approach.  
  Address Santiago de Compostela; España; June 2015  
  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 978-3-319-19389-2 Medium  
  Area Expedition Conference IbPRIA  
  Notes MILAB Approved no  
  Call Number Admin @ si @ BGR2015 Serial 2596  
Permanent link to this record
 

 
Author Estefania Talavera; Mariella Dimiccoli; Marc Bolaños; Maedeh Aghaei; Petia Radeva edit  doi
isbn  openurl
  Title R-clustering for egocentric video segmentation Type Conference Article
  Year 2015 Publication Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 Abbreviated Journal  
  Volume 9117 Issue (down) Pages 327-336  
  Keywords Temporal video segmentation; Egocentric videos; Clustering  
  Abstract In this paper, we present a new method for egocentric video temporal segmentation based on integrating a statistical mean change detector and agglomerative clustering(AC) within an energy-minimization framework. Given the tendency of most AC methods to oversegment video sequences when clustering their frames, we combine the clustering with a concept drift detection technique (ADWIN) that has rigorous guarantee of performances. ADWIN serves as a statistical upper bound for the clustering-based video segmentation. We integrate both techniques in an energy-minimization framework that serves to disambiguate the decision of both techniques and to complete the segmentation taking into account the temporal continuity of video frames descriptors. We present experiments over egocentric sets of more than 13.000 images acquired with different wearable cameras, showing that our method outperforms state-of-the-art clustering methods.  
  Address Santiago de Compostela; España; 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 LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-19389-2 Medium  
  Area Expedition Conference IbPRIA  
  Notes MILAB Approved no  
  Call Number Admin @ si @ TDB2015 Serial 2597  
Permanent link to this record
 

 
Author Manuel Graña; Bogdan Raducanu edit  doi
openurl 
  Title Special Issue on Bioinspired and knowledge based techniques and applications Type Journal Article
  Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume Issue (down) Pages 1-3  
  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 LAMP; Approved no  
  Call Number Admin @ si @ GrR2015 Serial 2598  
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Author C. Alejandro Parraga edit  isbn
openurl 
  Title Perceptual Psychophysics Type Book Chapter
  Year 2015 Publication Biologically-Inspired Computer Vision: Fundamentals and Applications Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor G.Cristobal; M.Keil; L.Perrinet  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-527-41264-8 Medium  
  Area Expedition Conference  
  Notes CIC; 600.074 Approved no  
  Call Number Admin @ si @ Par2015 Serial 2600  
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Author Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters edit  url
doi  isbn
openurl 
  Title Fractional Programming Weighted Decoding for Error-Correcting Output Codes Type Conference Article
  Year 2015 Publication Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 Abbreviated Journal  
  Volume Issue (down) Pages 38-50  
  Keywords  
  Abstract In order to increase the classification performance obtained using Error-Correcting Output Codes designs (ECOC), introducing weights in the decoding phase of the ECOC has attracted a lot of interest. In this work, we present a method for ECOC designs that focuses on increasing hypothesis margin on the data samples given a base classifier. While achieving this, we implicitly reward the base classifiers with high performance, whereas punish those with low performance. The resulting objective function is of the fractional programming type and we deal with this problem through the Dinkelbach’s Algorithm. The conducted tests over well known UCI datasets show that the presented method is superior to the unweighted decoding and that it outperforms the results of the state-of-the-art weighted decoding methods in most of the performed experiments.  
  Address Gunzburg; Germany; 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 ISBN 978-3-319-20247-1 Medium  
  Area Expedition Conference MCS  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ ISS2015 Serial 2601  
Permanent link to this record
 

 
Author Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro edit  url
openurl 
  Title Improving Bag of Visual Words Representations with Genetic Programming Type Conference Article
  Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords  
  Abstract The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains.
In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image
categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm.
 
  Address Killarney; Ireland; July 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 IJCNN  
  Notes HuPBA;MV Approved no  
  Call Number Admin @ si @ EME2015 Serial 2603  
Permanent link to this record
 

 
Author Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Alexander Statnikov; Evelyne Viegas edit  url
openurl 
  Title Design of the 2015 ChaLearn AutoML Challenge Type Conference Article
  Year 2015 Publication IEEE International Joint Conference on Neural Networks IJCNN2015 Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords  
  Abstract ChaLearn is organizing for IJCNN 2015 an Automatic Machine Learning challenge (AutoML) to solve classification and regression problems from given feature representations, without any human intervention. This is a challenge with code
submission: the code submitted can be executed automatically on the challenge servers to train and test learning machines on new datasets. However, there is no obligation to submit code. Half of the prizes can be won by just submitting prediction results.
There are six rounds (Prep, Novice, Intermediate, Advanced, Expert, and Master) in which datasets of progressive difficulty are introduced (5 per round). There is no requirement to participate in previous rounds to enter a new round. The rounds alternate AutoML phases in which submitted code is “blind tested” on
datasets the participants have never seen before, and Tweakathon phases giving time (' 1 month) to the participants to improve their methods by tweaking their code on those datasets. This challenge will push the state-of-the-art in fully automatic machine learning on a wide range of problems taken from real world
applications. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML
 
  Address Killarney; Ireland; July 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 IJCNN  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ GBC2015a Serial 2604  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño edit   pdf
doi  openurl
  Title WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians Type Journal Article
  Year 2015 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 43 Issue (down) Pages 99-111  
  Keywords Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection  
  Abstract We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice.  
  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 0895-6111 ISBN Medium  
  Area Expedition Conference  
  Notes MV; IAM; 600.047; 600.060; 600.075;SIAI Approved no  
  Call Number Admin @ si @ BSF2015 Serial 2609  
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Author Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell edit  openurl
  Title Quasi-real time digital assessment of Central Airway Obstruction Type Conference Article
  Year 2015 Publication 3rd European congress for bronchology and interventional pulmonology ECBIP2015 Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords  
  Abstract  
  Address Barcelona; Spain; April 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 ECBIP  
  Notes IAM; MV; 600.075 Approved no  
  Call Number SGT2015 Serial 2612  
Permanent link to this record
 

 
Author Antoni Gurgui; Debora Gil; Enric Marti edit  url
doi  isbn
openurl 
  Title Laplacian Unitary Domain for Texture Morphing Type Conference Article
  Year 2015 Publication Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 Abbreviated Journal  
  Volume 1 Issue (down) Pages 693-699  
  Keywords Facial; metamorphosis;LaplacianMorphing  
  Abstract Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.  
  Address Munich; Germany; February 2015  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-758-089-5 Medium  
  Area Expedition Conference VISAPP  
  Notes IAM; 600.075 Approved no  
  Call Number Admin @ si @ GGM2015 Serial 2614  
Permanent link to this record
 

 
Author Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen edit  openurl
  Title Quality Assessment of Optical Flow in Tagging MRI Type Conference Article
  Year 2015 Publication 5th Dutch Bio-Medical Engineering Conference BME2015 Abbreviated Journal  
  Volume Issue (down) Pages  
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  Abstract  
  Address The Netherlands; January 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 BME  
  Notes IAM; ADAS; 600.076; 600.075 Approved no  
  Call Number Admin @ si @ KMF2015 Serial 2616  
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Author Olivier Lefebvre; Pau Riba; Charles Fournier; Alicia Fornes; Josep Llados; Rejean Plamondon; Jules Gagnon-Marchand edit   pdf
url  openurl
  Title Monitoring neuromotricity on-line: a cloud computing approach Type Conference Article
  Year 2015 Publication 17th Conference of the International Graphonomics Society IGS2015 Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords  
  Abstract The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain.  
  Address Pointe-à-Pitre; Guadeloupe; June 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 IGS  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ LRF2015 Serial 2617  
Permanent link to this record
 

 
Author Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta edit   pdf
url  doi
isbn  openurl
  Title Large-scale Graph Indexing using Binary Embeddings of Node Contexts Type Conference Article
  Year 2015 Publication 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition Abbreviated Journal  
  Volume 9069 Issue (down) Pages 208-217  
  Keywords Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding  
  Abstract Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents.  
  Address Beijing; China; May 2015  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor C.-L.Liu; B.Luo; W.G.Kropatsch; J.Cheng  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-18223-0 Medium  
  Area Expedition Conference GbRPR  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ RLF2015a Serial 2618  
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Author Jorge Bernal; F. Javier Sanchez; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach edit  url
isbn  openurl
  Title Bulding up the future of colonoscopy: A synergy between clinicians and computer scientists Type Book Chapter
  Year 2015 Publication Colonoscopy and Colorectal Cancer Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords Intelligent systems; Image properties; Validation; Clinical drawbacks; Endoluminal scene description  
  Abstract Recent advances in endoscopic technology have generated an increasing interest in strengthening the collaboration between clinicians and computers scientist to develop intelligent systems that can provide additional information to clinicians in the different stages of an intervention. The objective of this chapter is to identify clinical drawbacks of colonoscopy in order to define potential areas of collaboration. Once areas are defined, we present the challenges that colonoscopy images present in order computational methods to provide with meaningful output, including those related to image formation and acquisition, as they are proven to have an impact in the performance of an intelligent system. Finally, we also propose how to define validation frameworks in order to assess the performance of a given method, making an special emphasis on how databases should be created and annotated and which metrics should be used to evaluate systems correctly.  
  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 978-953-51-2225-8 Medium  
  Area Expedition Conference  
  Notes MV Approved no  
  Call Number Admin @ si @ BSR2015 Serial 2624  
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Author Youssef El Rhabi; Simon Loic; Brun Luc edit   pdf
url  openurl
  Title Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel Type Conference Article
  Year 2015 Publication 15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015 Abbreviated Journal  
  Volume Issue (down) Pages  
  Keywords Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration  
  Abstract Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data.  
  Address Amiens; France; June 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 ORASIS  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ RLL2015 Serial 2626  
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