@inproceedings{560dae99662d40cf804ebca0f7a0d713,
title = "Action recognition using bag of features extracted from a beam of trajectories",
abstract = "A new spatio temporal descriptor is proposed for action recognition. The action is modelled from a beam of trajectories obtained using semi dense point tracking on the video sequence. We detect the dominant points of these trajectories as points of local extremum curvature and extract their corresponding feature vectors, to form a dictionary of atomic action elements. The high density of these informative and invariant elements allows effective statistical action description. Then, human action recognition is performed using a bag of feature model with SVM classifier. Experimentations show promising results on several well-known datasets.",
keywords = "action recognition, bag of features, dominant point, semi dense point tracking, spatio temporal feature, trajectory beam",
author = "Nguyen, \{Thanh Phuong\} and Antoine Manzanera",
year = "2013",
month = jan,
day = "1",
doi = "10.1109/ICIP.2013.6738897",
language = "English",
isbn = "9781479923410",
series = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
publisher = "IEEE Computer Society",
pages = "4354--4357",
booktitle = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
note = "2013 20th IEEE International Conference on Image Processing, ICIP 2013 ; Conference date: 15-09-2013 Through 18-09-2013",
}