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The Scientific World Journal
Volume 2014 (2014), Article ID 270171, 18 pages
Research Article

Episodic Reasoning for Vision-Based Human Action Recognition

1Computer Architecture and Network Group, School of Computer Science, University of Castilla-La Mancha, 13072 Ciudad Real, Spain
2The Institute of Electronics, Communications and Information Technology (ECIT), Queens University of Belfast, Belfast BT3 9DT, UK
3Digital Imaging Research Centre, Kingston University, London KT1 2EE, UK

Received 23 August 2013; Accepted 29 October 2013; Published 14 May 2014

Academic Editors: G. Bordogna and I. García

Copyright © 2014 Maria J. Santofimia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.