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Visual information-based activity recognition and fall detection for assisted living and ehealthcare

Yixiao Yun (Institutionen för signaler och system, Signalbehandling) ; Irene Y.H. Gu (Institutionen för signaler och system, Signalbehandling)
Elsevier Book: Ambient Assisted Living and Enhanced Living Environments: Principles, Technologies and Control p. 395-425. (2017)

Ambient intelligence for assisted living and healthcare has drawn increasing interest due to population aging across many countries. Challenges remain in developing robust methods for effective assisted living systems under complex real scenarios. Understanding/recognition of human activities is one of the fundamental issues in a human-centric smart environment, where visual data provides rich information on human behaviors including their interaction with other objects and surroundings. Real-time or near real-time visual information-based approaches offer effective analysis without the risk of invading the privacy, where videos are discarded after extracting features. This chapter mainly focuses on describing visual information-based daily activity recognition and anomaly detection through using low-resolution visual sensors. First, current state-of-the-art methods on visual activity recognition are briefly reviewed. Detailed descriptions are then given on three robust methods that exploit smooth manifolds. Manifold-based methods are attractive as human activity and context features can be efficiently represented by using low-dimensional smooth manifolds. Finally, experimental results and performance of several methods are given and compared, which provide further support to the robustness of manifold-based methods for visual activity recognition and anomaly detection. Information on some publicly available datasets is also included to facilitate the use of benchmark datasets for testing in the near future.

Nyckelord: Activity of daily living (ADL), Fall detection, Anomaly detection, Vision-based activity recognition, Ambient intelligence, Assisted living, Healthcare, Riemannian manifold

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Denna post skapades 2016-09-20. Senast ändrad 2017-07-04.
CPL Pubid: 242089


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Institutioner (Chalmers)

Institutionen för signaler och system, Signalbehandling (1900-2017)


Informations- och kommunikationsteknik
Datorseende och robotik (autonoma system)
Robotteknik och automation

Chalmers infrastruktur

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Riemannian Manifold-Based Modeling and Classification Methods for Video Activities with Applications to Assisted Living and Smart Home