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Author Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria edit  url
isbn  openurl
  Title Visual Content Layer for Scalable Recognition in Urban Image Databases, Internet Multimedia Search and Mining Type Conference Article
  Year 2009 Publication (up) 10th IEEE International Conference on Multimedia and Expo Abbreviated Journal  
  Volume Issue Pages 1616–1619  
  Keywords  
  Abstract Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (> 500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. This allows an efficient and scalable way of accessing maps by visual content.  
  Address New York (USA)  
  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 978-1-4244-4291-1 Medium  
  Area Expedition Conference ICME  
  Notes OR;MILAB;HuPBA;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ BER2009 Serial 1189  
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Author D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez edit  doi
isbn  openurl
  Title Characterizing conversational group dynamics using nonverbal behaviour Type Conference Article
  Year 2009 Publication (up) 10th IEEE International Conference on Multimedia and Expo Abbreviated Journal  
  Volume Issue Pages 370–373  
  Keywords  
  Abstract This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%.  
  Address New York, USA  
  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 1945-7871 ISBN 978-1-4244-4290-4 Medium  
  Area Expedition Conference ICME  
  Notes OR;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ JRG2009 Serial 1217  
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