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Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  openurl
  Title (down) Automatic Learning of Conceptual Knowledge for the Interpretation of Human Behavior in Video Sequences Type Book Chapter
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:507–514 Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Girona (Spain)  
  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  
  Notes ISE Approved no  
  Call Number ISE @ ise @ BFR2007 Serial 807  
Permanent link to this record
 
 
Author Carles Fernandez; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title (down) Automatic Learning of Background Semantics in Generic Surveilled Scenes Type Conference Article
  Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal  
  Volume 6313 Issue II Pages 678–692  
  Keywords  
  Abstract Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis.  
  Address Crete (Greece)  
  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 978-3-642-15551-2 Medium  
  Area Expedition Conference ECCV  
  Notes ISE Approved no  
  Call Number ISE @ ise @ FGR2010 Serial 1439  
Permanent link to this record
 
 
Author Ignasi Rius; Jordi Gonzalez; Mikhail Mozerov; Xavier Roca edit  openurl
  Title (down) Automatic Learning of 3D Pose Variability in Walking Performances for Gait Analysis Type Journal
  Year 2008 Publication International Journal for Computational Vision and Biomechanics Abbreviated Journal  
  Volume 1 Issue 1 Pages 33–43  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ RGM2008 Serial 1020  
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Author Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett edit  openurl
  Title (down) Automatic Labeling of Colonoscopy Video for Cancer Detection Type Conference Article
  Year 2007 Publication In Proc. berian Conference, IbPRIA Abbreviated Journal  
  Volume Issue Pages 290-297  
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  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV;SIAI Approved no  
  Call Number fernando @ fernando @ Serial 2431  
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Author Jordi Gonzalez; X. Varona; Xavier Roca; Juan J. Villanueva edit  openurl
  Title (down) Automatic Keyframing of Human Actions for Computer Animation Type Miscellaneous
  Year 2003 Publication Abbreviated Journal  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ GVR2003a Serial 359  
Permanent link to this record
 
 
Author Jordi Gonzalez; J. Varona; Xavier Roca; Juan J. Villanueva edit  openurl
  Title (down) Automatic Keyframing of Human Actions for Computer Animation Type Miscellaneous
  Year 2003 Publication In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science 2652:287–296 Abbreviated Journal  
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  Address Springer-Verlag  
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  Notes ISE Approved no  
  Call Number ISE @ ise @ GVR2003b Serial 381  
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Author Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez edit  doi
isbn  openurl
  Title (down) Automatic Key Pose Selection for 3D Human Action Recognition Type Conference Article
  Year 2010 Publication 6th International Conference on Articulated Motion and Deformable Objects Abbreviated Journal  
  Volume 6169 Issue Pages 290–299  
  Keywords  
  Abstract This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition.  
  Address  
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  Publisher Springer Verlag Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-14060-0 Medium  
  Area Expedition Conference AMDO  
  Notes ISE Approved no  
  Call Number DAG @ dag @ GBR2010 Serial 1317  
Permanent link to this record
 
 
Author Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit  url
openurl 
  Title (down) Automatic Key Frames Detection in Intravascular Ultrasound Sequences Type Conference Article
  Year 2011 Publication In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging Abbreviated Journal  
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  Abstract We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events.  
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  Area Expedition Conference CVII  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPB2011 Serial 1767  
Permanent link to this record
 
 
Author Ellen J.L. Brunenberg; Oriol Pujol; Bart M. Ter Haar Romeny; Petia Radeva edit  doi
openurl 
  Title (down) Automatic IVUS Segmentation of Atherosclerotic Plaque with Stop & Go Snake Type Miscellaneous
  Year 2006 Publication 9th International Conference on Medical Image Computing and Computer–Assisted Intervention (MICCAI´06), 9–16 Abbreviated Journal  
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  Address Copenhagen (Denmark)  
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  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ BPT2006 Serial 767  
Permanent link to this record
 
 
Author Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados edit  openurl
  Title (down) Automatic Interpretation of Proofreading Sketches Type Miscellaneous
  Year 2006 Publication 3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 35–42 Abbreviated Journal  
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  Address Vienna (Austria)  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ RSL2006a Serial 716  
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Author Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title (down) Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder Type Conference Article
  Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume 7325 Issue II Pages 222-229  
  Keywords  
  Abstract Poster
Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.		  
  Address Aveiro, Portugal  
  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 978-3-642-31297-7 Medium  
  Area Expedition Conference ICIAR  
  Notes OR; HuPBA; MILAB Approved no  
  Call Number Admin @ si @ ISG2012 Serial 2059  
Permanent link to this record
 
 
Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner edit  openurl
  Title (down) Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Journal
  Year 2011 Publication e-Perimetron Abbreviated Journal ePER  
  Volume 6 Issue 4 Pages 219-229  
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  Abstract By means of computer vision algorithms scanned images of maps are processed in order to extract relevant geographic information from printed coordinate pairs. The meaningful information is then transformed into georeferencing information for each single map sheet, and the complete set is compiled to produce a graphical index sheet for the map series along with relevant metadata. The whole process is fully automated and trained to attain maximum effectivity and throughput.  
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  Notes DAG Approved no  
  Call Number Admin @ si @ RRL2011a Serial 1765  
Permanent link to this record
 
 
Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner edit  openurl
  Title (down) Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Conference Article
  Year 2011 Publication In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage Abbreviated Journal  
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  ISSN ISBN Medium  
  Area Expedition Conference CartoHerit  
  Notes DAG Approved no  
  Call Number Admin @ si @ RRL2011b Serial 1978  
Permanent link to this record
 
 
Author Victoria Ruiz; Angel Sanchez; Jose F. Velez; Bogdan Raducanu edit   pdf
url  openurl
  Title (down) Automatic Image-Based Waste Classification Type Conference Article
  Year 2019 Publication International Work-Conference on the Interplay Between Natural and Artificial Computation. From Bioinspired Systems and Biomedical Applications to Machine Learning Abbreviated Journal  
  Volume 11487 Issue Pages 422–431  
  Keywords Computer Vision; Deep learning; Convolutional neural networks; Waste classification  
  Abstract The management of solid waste in large urban environments has become a complex problem due to increasing amount of waste generated every day by citizens and companies. Current Computer Vision and Deep Learning techniques can help in the automatic detection and classification of waste types for further recycling tasks. In this work, we use the TrashNet dataset to train and compare different deep learning architectures for automatic classification of garbage types. In particular, several Convolutional Neural Networks (CNN) architectures were compared: VGG, Inception and ResNet. The best classification results were obtained using a combined Inception-ResNet model that achieved 88.6% of accuracy. These are the best results obtained with the considered dataset.  
  Address Almeria; June 2019  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IWINAC  
  Notes LAMP; 600.120 Approved no  
  Call Number RSV2019 Serial 3273  
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Author Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera edit  openurl
  Title (down) Automatic Human Behavior Analysis in ADHD Type Conference Article
  Year 2012 Publication Eunethydis 2nd International ADHD Conference Abbreviated Journal  
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  Area Expedition Conference EUNETHYDIS  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ EMI2012a Serial 2058  
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