Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions

Johanna Carvajal, Arnold Wiliem, Chris McCool, Brian C. Lovell, Conrad Sanderson. Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions. In Huiping Cao, Jinyan Li, Ruili Wang, editors, Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF Auckland, New Zealand, April 19, 2016, Revised Selected Papers. Volume 9794 of Lecture Notes in Computer Science, pages 88-100, Springer, 2016. [doi]

@inproceedings{CarvajalWMLS16,
  title = {Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions},
  author = {Johanna Carvajal and Arnold Wiliem and Chris McCool and Brian C. Lovell and Conrad Sanderson},
  year = {2016},
  doi = {10.1007/978-3-319-42996-0_8},
  url = {http://dx.doi.org/10.1007/978-3-319-42996-0_8},
  researchr = {https://researchr.org/publication/CarvajalWMLS16},
  cites = {0},
  citedby = {0},
  pages = {88-100},
  booktitle = {Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF Auckland, New Zealand, April 19, 2016, Revised Selected Papers},
  editor = {Huiping Cao and Jinyan Li and Ruili Wang},
  volume = {9794},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-42995-3},
}