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Sensors 2016, 16(1), 72; doi:10.3390/s16010072

Recognition of Activities of Daily Living with Egocentric Vision: A Review

Faculty of Science, Engineering and Computing, Kingston University, Kingston upon Thames, London KT1 2EE, UK
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Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 4 November 2015 / Revised: 18 December 2015 / Accepted: 26 December 2015 / Published: 7 January 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [17045 KB, uploaded 8 January 2016]   |  

Abstract

Video-based recognition of activities of daily living (ADLs) is being used in ambient assisted living systems in order to support the independent living of older people. However, current systems based on cameras located in the environment present a number of problems, such as occlusions and a limited field of view. Recently, wearable cameras have begun to be exploited. This paper presents a review of the state of the art of egocentric vision systems for the recognition of ADLs following a hierarchical structure: motion, action and activity levels, where each level provides higher semantic information and involves a longer time frame. The current egocentric vision literature suggests that ADLs recognition is mainly driven by the objects present in the scene, especially those associated with specific tasks. However, although object-based approaches have proven popular, object recognition remains a challenge due to the intra-class variations found in unconstrained scenarios. As a consequence, the performance of current systems is far from satisfactory. View Full-Text
Keywords: egocentric vision; wearable cameras; ambient assisted living; activity recognition egocentric vision; wearable cameras; ambient assisted living; activity recognition
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. (CC BY 4.0).

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MDPI and ACS Style

Nguyen, T.-H.-C.; Nebel, J.-C.; Florez-Revuelta, F. Recognition of Activities of Daily Living with Egocentric Vision: A Review. Sensors 2016, 16, 72.

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