Recognizing human actions: a local SVM approach

@article{Schldt2004RecognizingHA,
  title={Recognizing human actions: a local SVM approach},
  author={Christian Sch{\"u}ldt and Ivan Laptev and Barbara Caputo},
  journal={Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.},
  year={2004},
  volume={3},
  pages={32-36 Vol.3}
}
Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper, we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-time features and integrate such representations with SVM classification schemes for recognition. For the purpose of evaluation we introduce a new video database containing 2391 sequences of six human… CONTINUE READING
Highly Influential
This paper has highly influenced 580 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 3,518 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.
2,058 Citations
15 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 2,058 extracted citations

3,519 Citations

0200400'06'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 3,519 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…