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Author (up) Victor Ponce; Hugo Jair Escalante; Sergio Escalera; Xavier Baro edit   pdf
url  doi
openurl 
  Title Gesture and Action Recognition by Evolved Dynamic Subgestures Type Conference Article
  Year 2015 Publication 26th British Machine Vision Conference Abbreviated Journal  
  Volume Issue Pages 129.1-129.13  
  Keywords  
  Abstract This paper introduces a framework for gesture and action recognition based on the evolution of temporal gesture primitives, or subgestures. Our work is inspired on the principle of producing genetic variations within a population of gesture subsequences, with the goal of obtaining a set of gesture units that enhance the generalization capability of standard gesture recognition approaches. In our context, gesture primitives are evolved over time using dynamic programming and generative models in order to recognize complex actions. In few generations, the proposed subgesture-based representation
of actions and gestures outperforms the state of the art results on the MSRDaily3D and MSRAction3D datasets.
 
  Address Swansea; uk; September 2015  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference BMVC  
  Notes HuPBA;MV Approved no  
  Call Number Admin @ si @ PEE2015 Serial 2657  
Permanent link to this record
 

 
Author (up) Victor Ponce; Sergio Escalera; Marc Perez; Oriol Janes; Xavier Baro edit  doi
openurl 
  Title Non-Verbal Communication Analysis in Victim-Offender Mediations Type Journal Article
  Year 2015 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 67 Issue 1 Pages 19-27  
  Keywords Victim–Offender Mediation; Multi-modal human behavior analysis; Face and gesture recognition; Social signal processing; Computer vision; Machine learning  
  Abstract We present a non-invasive ambient intelligence framework for the semi-automatic analysis of non-verbal communication applied to the restorative justice field. We propose the use of computer vision and social signal processing technologies in real scenarios of Victim–Offender Mediations, applying feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues from the fields of psychology and observational methodology. We test our methodology on data captured in real Victim–Offender Mediation sessions in Catalonia. We define the ground truth based on expert opinions when annotating the observed social responses. Using different state of the art binary classification approaches, our system achieves recognition accuracies of 86% when predicting satisfaction, and 79% when predicting both agreement and receptivity. Applying a regression strategy, we obtain a mean deviation for the predictions between 0.5 and 0.7 in the range [1–5] for the computed social signals.  
  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 HuPBA;MV Approved no  
  Call Number Admin @ si @ PEP2015 Serial 2583  
Permanent link to this record
 

 
Author (up) Wenjuan Gong; W.Zhang; Jordi Gonzalez; Y.Ren; Z.Li edit  doi
openurl 
  Title Enhanced Asymmetric Bilinear Model for Face Recognition Type Journal Article
  Year 2015 Publication 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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  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 (up) Wenjuan Gong; Y.Huang; Jordi Gonzalez; Liang Wang edit  openurl
  Title An Effective Solution to Double Counting Problem in Human Pose Estimation Type Miscellaneous
  Year 2015 Publication Arxiv Abbreviated Journal  
  Volume Issue Pages  
  Keywords Pose estimation; double counting problem; mix-ture of parts Model  
  Abstract The mixture of parts model has been successfully applied to solve the 2D
human pose estimation problem either as an explicitly trained body part model
or as latent variables for pedestrian detection. Even in the era of massive
applications of deep learning techniques, the mixture of parts model is still
effective in solving certain problems, especially in the case with limited
numbers of training samples. In this paper, we consider using the mixture of
parts model for pose estimation, wherein a tree structure is utilized for
representing relations between connected body parts. This strategy facilitates
training and inferencing of the model but suffers from double counting
problems, where one detected body part is counted twice due to lack of
constrains among unconnected body parts. To solve this problem, we propose a
generalized solution in which various part attributes are captured by multiple
features so as to avoid the double counted problem. Qualitative and
quantitative experimental results on a public available dataset demonstrate the
effectiveness of our proposed method.

An Effective Solution to Double Counting Problem in Human Pose Estimation – ResearchGate. Available from: http://www.researchgate.net/publication/271218491AnEffectiveSolutiontoDoubleCountingProbleminHumanPose_Estimation [accessed Oct 22, 2015].
 
  Address  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ISE; 600.078 Approved no  
  Call Number Admin @ si @ GHG2015 Serial 2590  
Permanent link to this record
 

 
Author (up) Xavier Baro; Jordi Gonzalez; Junior Fabian; Miguel Angel Bautista; Marc Oliu; Hugo Jair Escalante; Isabelle Guyon; Sergio Escalera edit  doi
openurl 
  Title ChaLearn Looking at People 2015 challenges: action spotting and cultural event recognition Type Conference Article
  Year 2015 Publication 2015 IEEE Conference on Computer Vision and Pattern Recognition Worshops (CVPRW) Abbreviated Journal  
  Volume Issue Pages 1-9  
  Keywords  
  Abstract Following previous series on Looking at People (LAP) challenges [6, 5, 4], ChaLearn ran two competitions to be presented at CVPR 2015: action/interaction spotting and cultural event recognition in RGB data. We ran a second round on human activity recognition on RGB data sequences. In terms of cultural event recognition, tens of categories have to be recognized. This involves scene understanding and human analysis. This paper summarizes the two performed challenges and obtained results. Details of the ChaLearn LAP competitions can be found at http://gesture.chalearn.org/.  
  Address Boston; EEUU; June 2015  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference CVPRW  
  Notes HuPBA;MV Approved no  
  Call Number Serial 2652  
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Author (up) Xavier Otazu; Olivier Penacchio; Xim Cerda-Company edit  url
openurl 
  Title Brightness and colour induction through contextual influences in V1 Type Conference Article
  Year 2015 Publication Scottish Vision Group 2015 SGV2015 Abbreviated Journal  
  Volume 12 Issue 9 Pages 1208-2012  
  Keywords  
  Abstract  
  Address Carnoustie; Scotland; March 2015  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SGV  
  Notes NEUROBIT; Approved no  
  Call Number Admin @ si @ OPC2015a Serial 2632  
Permanent link to this record
 

 
Author (up) Xavier Otazu; Olivier Penacchio; Xim Cerda-Company edit  openurl
  Title An excitatory-inhibitory firing rate model accounts for brightness induction, colour induction and visual discomfort Type Conference Article
  Year 2015 Publication Barcelona Computational, Cognitive and Systems Neuroscience Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Barcelona; June 2015  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference BARCCSYN  
  Notes NEUROBIT; Approved no  
  Call Number Admin @ si @ OPC2015b Serial 2634  
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Author (up) 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 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  
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  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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