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Author (up) Mohammad Ali Bagheri; Gang Hu; Qigang Gao; Sergio Escalera edit   pdf
doi  openurl
  Title A Framework of Multi-Classifier Fusion for Human Action Recognition Type Conference Article
  Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1260 - 1265  
  Keywords  
  Abstract The performance of different action-recognition methods using skeleton joint locations have been recently studied by several computer vision researchers. However, the potential improvement in classification through classifier fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of five action learning techniques, each performing the recognition task from a different perspective. The underlying rationale of the fusion approach is that different learners employ varying structures of input descriptors/features to be trained. These varying structures cannot be attached and used by a single learner. In addition, combining the outputs of several learners can reduce the risk of an unfortunate selection of a poorly performing learner. This leads to having a more robust and general-applicable framework. Also, we propose two simple, yet effective, action description techniques. In order to improve the recognition performance, a powerful combination strategy is utilized based on the Dempster-Shafer theory, which can effectively make use of diversity of base learners trained on different sources of information. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers' output, showing advanced performance of the proposed methodology.  
  Address Stockholm; Sweden; August 2014  
  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 1051-4651 ISBN Medium  
  Area Expedition Conference ICPR  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ BHG2014 Serial 2446  
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