Sparse coding-based space-time video representation for action recognition
作者: Yinghua FuTao ZhangWenjin Wang
作者单位: 1Shanghai Jiao Tong University
2University of Shanghai for Science and Technology
刊名: Multimedia Tools and Applications, 2017, Vol.76 (10), pp.12645-12658
来源数据库: Springer Nature Journal
DOI: 10.1007/s11042-016-3630-9
关键词: Sparse codingSpace-time saliencyAction recognitionSelf-informationShannon entropy
原始语种摘要: Methods based on feature descriptors around local interest points are now widely used in action recognition. Feature points are detected using a number of measures, namely saliency, periodicity, motion activity etc. Each of these measures is usually intensity-based and provides a trade-off between density and informativeness. In this paper, we address the problem of action recognition by representing image sequences as a sparse collection of patch-level space-time events that are salient in both space and time domain. Our method uses a multi-scale volumetric representation of video and adaptively selects an optimal space-time scale under which the saliency of a patch is most significant. The input image sequences are first partitioned into non-overlapping patches. Then, each patch is...
全文获取路径: Springer Nature  (合作)
影响因子:1.014 (2012)

  • recognition 识别
  • coding 编码
  • action 行为
  • video 影象
  • patch 斑点
  • representation 表现
  • entropy 平均信息量
  • representing 表示
  • Action 
  • demonstrate 说明