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Author David Masip; Michael S. North ; Alexander Todorov; Daniel N. Osherson edit   pdf
doi  openurl
  Title Automated Prediction of Preferences Using Facial Expressions Type Journal Article
  Year 2014 Publication PloS one Abbreviated Journal Plos  
  Volume 9 Issue 2 Pages e87434  
  Keywords  
  Abstract We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers’ preferences between images (e.g., of celebrities) based on covert videos of the observers’ faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available.  
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  Notes OR;MV Approved no  
  Call Number Admin @ si @ MNT2014 Serial 2453  
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Author Laura Igual; Agata Lapedriza; Ricard Borras edit   pdf
doi  openurl
  Title Robust Gait-Based Gender Classification using Depth Cameras Type Journal Article
  Year 2013 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume 37 Issue 1 Pages 72-80  
  Keywords  
  Abstract This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section.  
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  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ ILB2013 Serial 2144  
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Author Onur Ferhat; Fernando Vilariño edit   pdf
doi  openurl
  Title Low Cost Eye Tracking: The Current Panorama Type Journal Article
  Year 2016 Publication Computational Intelligence and Neuroscience Abbreviated Journal CIN  
  Volume Issue Pages Article ID 8680541  
  Keywords  
  Abstract Despite the availability of accurate, commercial gaze tracker devices working with infrared (IR) technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements. Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques. We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications. With all this information, we aim to provide the contemporary and future researchers with a map detailing previously explored ideas and the required tools.  
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  Area Expedition Conference  
  Notes MV; 605.103; 600.047; 600.097;SIAI Approved no  
  Call Number Admin @ si @ FeV2016 Serial 2744  
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Author Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey edit  doi
openurl 
  Title Automatic segmentation and inpainting of specular highlights for endoscopic imaging Type Journal Article
  Year 2010 Publication EURASIP Journal on Image and Video Processing Abbreviated Journal EURASIP JIVP  
  Volume 2010 Issue 9 Pages  
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  ISSN ISBN Medium  
  Area 800 Expedition Conference  
  Notes MV Approved no  
  Call Number fernando @ fernando @ Serial 2423  
Permanent link to this record
 

 
Author Sergio Escalera; Oriol Pujol; Petia Radeva; Jordi Vitria; Maria Teresa Anguera edit  doi
openurl 
  Title Automatic Detection of Dominance and Expected Interest Type Journal Article
  Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages 12  
  Keywords  
  Abstract Article ID 491819
Social Signal Processing is an emergent area of research that focuses on the analysis of social constructs. Dominance and interest are two of these social constructs. Dominance refers to the level of influence a person has in a conversation. Interest, when referred in terms of group interactions, can be defined as the degree of engagement that the members of a group collectively display during their interaction. In this paper, we argue that only using behavioral motion information, we are able to predict the interest of observers when looking at face-to-face interactions as well as the dominant people. First, we propose a simple set of movement-based features from body, face, and mouth activity in order to define a higher set of interaction indicators. The considered indicators are manually annotated by observers. Based on the opinions obtained, we define an automatic binary dominance detection problem and a multiclass interest quantification problem. Error-Correcting Output Codes framework is used to learn to rank the perceived observer's interest in face-to-face interactions meanwhile Adaboost is used to solve the dominant detection problem. The automatic system shows good correlation between the automatic categorization results and the manual ranking made by the observers in both dominance and interest detection problems.
 
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  ISSN 1110-8657 ISBN Medium  
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  Notes OR;MILAB;HUPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010d Serial 1283  
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