@inproceedings{fd150679bf0e405787453abda1f23678,
title = "Human action recognition in stereoscopic videos based on bag of features and disparity pyramids",
abstract = "In this paper, we propose a method for human action recognition in unconstrained environments based on stereoscopic videos. We describe a video representation scheme that exploits the enriched visual and disparity information that is available for such data. Each stereoscopic video is represented by multiple vectors, evaluated on video locations corresponding to different disparity zones. By using these vectors, multiple action descriptions can be determined that either correspond to specific disparity zones, or combine information appearing in different disparity zones in the classification phase. Experimental results denote that the proposed approach enhances action classification performance, when compared to the standard approach, and achieves state-of-the-art performance on the Hollywood 3D database designed for the recognition of complex actions in unconstrained environments.",
keywords = "Human Action Recognition, Stereoscopic Videos, Disparity Pyramids, Bag of Features",
author = "Alexandros Iosifidis and Anastasios Tefas and Nikos Nikolaidis and Ioannis Pitas",
year = "2015",
month = jan,
language = "English",
isbn = "9781479946037",
series = "Proceedings of the European Signal Processing Conference (EUSIPCO)",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "1317--1321",
booktitle = "2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO 2014)",
address = "United States",
note = "22nd European Signal Processing Conference, EUSIPCO 2014 ; Conference date: 01-09-2014 Through 05-09-2014",
}