International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064




Downloads: 117 | Views: 216

Survey Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014 | Rating: 6.7 / 10


A Survey Paper on Learning Pullback HMM Distance for Recognition of Action

Vanita Babane [3] | Poonam Sangar


Abstract: Recent work in action recognition has exposed the limitations of features extracted from spatiotemporal video volumes. Whereas, encoding the actions dynamics using generative dynamical models has a number of attractive features, in this respect Hidden Markov models (HMMs) is a popular choice. A general framework based on pullback metrics for learning distance functions of a given training set of labeled videos has been generated, The optimal distance function is selected among a family of pullback ones, which is generated by a parameterized automorphism of the space models. An experimental result shows that how pullback learning greatly improves action recognition performances with respect to base distances.


Keywords: Distance learning, pullback metrics, hidden Markov models HMM, action recognition


Edition: Volume 3 Issue 11, November 2014,


Pages: 2225 - 2226



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