Using Common Spatial Patterns to Select Relevant Pixels for Video Activity Recognition
View/ Open
Date
2020-11-14Author
Rodríguez Moreno, Itsaso
Martínez Otzeta, José María
Irigoyen Garbizu, Itziar
Goienetxea Urkizu, Izaro
Metadata
Show full item record
Applied Sciences 10(22) : (2020) // Article ID 8075
Abstract
first_page
settings
Open AccessArticle
Using Common Spatial Patterns to Select Relevant Pixels for Video Activity Recognition
by Itsaso Rodríguez-Moreno
* [OrcID] , José María Martínez-Otzeta
[OrcID] , Basilio Sierra
[OrcID] , Itziar Irigoien
, Igor Rodriguez-Rodriguez
and Izaro Goienetxea
[OrcID]
Department of Computer Science and Artificial Intelligence, University of the Basque Country, Manuel Lardizabal 1, 20018 Donostia-San Sebastián, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(22), 8075; https://doi.org/10.3390/app10228075
Received: 1 October 2020 / Revised: 30 October 2020 / Accepted: 11 November 2020 / Published: 14 November 2020
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology Ⅱ)
Download PDF Browse Figures
Abstract
Video activity recognition, despite being an emerging task, has been the subject of important research due to the importance of its everyday applications. Video camera surveillance could benefit greatly from advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. In this paper, a new approach for video action recognition is presented. The new technique consists of introducing a method, which is usually used in Brain Computer Interface (BCI) for electroencephalography (EEG) systems, and adapting it to this problem. After describing the technique, achieved results are shown and a comparison with another method is carried out to analyze the performance of our new approach.
Collections
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).