Multimedia Tools and Applications

, Volume 77, Issue 3, pp 3279–3286 | Cite as

Investigating image stitching for action recognition

  • Yufeng Li
  • Ping’an Li
  • Daozhong Lei
  • Yingchun Shi
  • Lixin Tan


Action recognition is usually a central problem for many practical applications, such as video annotations, video surveillance and human computer interaction. Most action recognition approaches are based on localized spatio-temporal features that can vary significantly when the viewpoint changes. However, their performance rapidly drops when the viewpoints of the training and testing data are different. In this paper, we propose a transfer learning framework for view-invariant action recognition by the way of sharing image stitching feature among different views. Experimental results on multi-view action recognition IXMAS dataset demonstrate that our method produces remarkably good results and outperforms baseline methods.


Image stitching Transfer learning Action recognition 



This research is supported by the Scientific Research Project of Hunan Provincial Education Department, China. The research and application of UAV Aerial system based on image splicing using multiple cameras (Grant No. 16C1139).


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Yufeng Li
    • 1
  • Ping’an Li
    • 1
  • Daozhong Lei
    • 1
  • Yingchun Shi
    • 1
  • Lixin Tan
    • 1
  1. 1.School of Electronic EngineeringHunan College of InformationHunanChina

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