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Author Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit  url
openurl 
  Title (up) 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  
  Volume Issue Pages  
  Keywords  
  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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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVII  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPB2011 Serial 1767  
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Author Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez edit  doi
isbn  openurl
  Title (up) 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  
  Corporate Author Thesis  
  Publisher Springer Verlag 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 978-3-642-14060-0 Medium  
  Area Expedition Conference AMDO  
  Notes ISE Approved no  
  Call Number DAG @ dag @ GBR2010 Serial 1317  
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Author Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva edit  openurl
  Title (up) Automatic Keyframing of Human Actions for Computer Animation Type Miscellaneous
  Year 2003 Publication Abbreviated Journal  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ GVR2003a Serial 359  
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Author Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva edit  openurl
  Title (up) 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  
  Volume Issue Pages  
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  Abstract  
  Address Springer-Verlag  
  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 Approved no  
  Call Number ISE @ ise @ GVR2003b Serial 381  
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Author Fernando Vilariño; Gerard Lacey; Jiang Zhou; Hugh Mulcahy; Stephen Patchett edit  openurl
  Title (up) 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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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV;SIAI Approved no  
  Call Number fernando @ fernando @ Serial 2431  
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Author Ignasi Rius; Jordi Gonzalez; Mikhail Mozerov; Xavier Roca edit  openurl
  Title (up) 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 Carles Fernandez; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title (up) 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  
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Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  openurl
  Title (up) 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  
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  Address Girona (Spain)  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ BFR2007 Serial 807  
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Author Joan Mas; B. Lamiroy; Gemma Sanchez; Josep Llados edit  openurl
  Title (up) Automatic Learning of Symbol Descriptions Avoiding Topological Ambiguities Type Miscellaneous
  Year 2006 Publication 3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 27–34 Abbreviated Journal  
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  Address Vienna (Austria)  
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  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ MLS2006b Serial 710  
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Author Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit   pdf
doi  isbn
openurl 
  Title (up) Automatic Non-Rigid Temporal Alignment of IVUS Sequences Type Conference Article
  Year 2012 Publication 15th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 1 Issue Pages 642-650  
  Keywords  
  Abstract Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability.  
  Address Nice, France  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-33414-6 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ABC2012 Serial 2168  
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Author Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit  url
doi  openurl
  Title (up) Automatic non-rigid temporal alignment of IVUS sequences: method and quantitative validation Type Journal Article
  Year 2013 Publication Ultrasound in Medicine and Biology Abbreviated Journal UMB  
  Volume 39 Issue 9 Pages 1698-712  
  Keywords Intravascular ultrasound; Dynamic time warping; Non-rigid alignment; Sequence matching; Partial overlapping strategy  
  Abstract Clinical studies on atherosclerosis regression/progression performed by intravascular ultrasound analysis would benefit from accurate alignment of sequences of the same patient before and after clinical interventions and at follow-up. In this article, a methodology for automatic alignment of intravascular ultrasound sequences based on the dynamic time warping technique is proposed. The non-rigid alignment is adapted to the specific task by applying it to multidimensional signals describing the morphologic content of the vessel. Moreover, dynamic time warping is embedded into a framework comprising a strategy to address partial overlapping between acquisitions and a term that regularizes non-physiologic temporal compression/expansion of the sequences. Extensive validation is performed on both synthetic and in vivo data. The proposed method reaches alignment errors of approximately 0.43 mm for pairs of sequences acquired during the same intervention phase and 0.77 mm for pairs of sequences acquired at successive intervention stages.  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ABC2013 Serial 2313  
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Author Alvaro Cepero; Albert Clapes; Sergio Escalera edit   pdf
doi  openurl
  Title (up) Automatic non-verbal communication skills analysis: a quantitative evaluation Type Journal Article
  Year 2015 Publication AI Communications Abbreviated Journal AIC  
  Volume 28 Issue 1 Pages 87-101  
  Keywords Social signal processing; human behavior analysis; multi-modal data description; multi-modal data fusion; non-verbal communication analysis; e-Learning  
  Abstract The oral communication competence is defined on the top of the most relevant skills for one's professional and personal life. Because of the importance of communication in our activities of daily living, it is crucial to study methods to evaluate and provide the necessary feedback that can be used in order to improve these communication capabilities and, therefore, learn how to express ourselves better. In this work, we propose a system capable of evaluating quantitatively the quality of oral presentations in an automatic fashion. The system is based on a multi-modal RGB, depth, and audio data description and a fusion approach in order to recognize behavioral cues and train classifiers able to eventually predict communication quality levels. The performance of the proposed system is tested on a novel dataset containing Bachelor thesis' real defenses, presentations from an 8th semester Bachelor courses, and Master courses' presentations at Universitat de Barcelona. Using as groundtruth the marks assigned by actual instructors, our system achieves high performance categorizing and ranking presentations by their quality, and also making real-valued mark predictions.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0921-7126 ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA;MILAB Approved no  
  Call Number Admin @ si @ CCE2015 Serial 2549  
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Author J.L. Pech-Pacheco; J. Alvarez-Borrego; Gabriel Cristobal; Matthias S. Keil edit  openurl
  Title (up) Automatic object identification irrespective to geometric changes Type Journal
  Year 2003 Publication Optical Engineering, 42(2): 551–559 (IF: 0.877) Abbreviated Journal  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number Admin @ si @ PAC2003 Serial 632  
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Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria edit  doi
isbn  openurl
  Title (up) Automatic Point-based Facial Trait Judgments Evaluation Type Conference Article
  Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2715–2720  
  Keywords  
  Abstract Humans constantly evaluate the personalities of other people using their faces. Facial trait judgments have been studied in the psychological field, and have been determined to influence important social outcomes of our lives, such as elections outcomes and social relationships. Recent work on textual descriptions of faces has shown that trait judgments are highly correlated. Further, behavioral studies suggest that two orthogonal dimensions, valence and dominance, can describe the basis of the human judgments from faces. In this paper, we used a corpus of behavioral data of judgments on different trait dimensions to automatically learn a trait predictor from facial pixel images. We study whether trait evaluations performed by humans can be learned using machine learning classifiers, and used later in automatic evaluations of new facial images. The experiments performed using local point-based descriptors show promising results in the evaluation of the main traits.  
  Address San Francisco CA, USA  
  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 1063-6919 ISBN 978-1-4244-6984-0 Medium  
  Area Expedition Conference CVPR  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RMT2010 Serial 1282  
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Author Mario Rojas; David Masip; A. Todorov; Jordi Vitria edit  url
doi  openurl
  Title (up) Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models Type Journal Article
  Year 2011 Publication PloS one Abbreviated Journal Plos  
  Volume 6 Issue 8 Pages e23323  
  Keywords  
  Abstract JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions
 
  Address  
  Corporate Author Thesis  
  Publisher Public Library of Science 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 OR;MV Approved no  
  Call Number Admin @ si @ RMT2011 Serial 1883  
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