Applying a 3D qualitative trajectory calculus to human action recognition using depth cameras

Coppola, Claudio and Martinez Mozos, Oscar and Bellotto, Nicola (2015) Applying a 3D qualitative trajectory calculus to human action recognition using depth cameras. In: IEEE/RSJ IROS Workshop on Assistance and Service Robotics in a Human Environment, 28 September - 3 October 2015, Hamburg, Germany.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

Abstract

The life span of ordinary people is increasing steadily and many developed countries are facing the big challenge of dealing with an ageing population at greater risk of impairments and cognitive disorders, which hinder their quality of life. Monitoring human activities of daily living (ADLs) is important in order to identify potential health problems and apply corrective strategies as soon as possible. Towards this long term goal, the research here presented is a first step to monitor ADLs using 3D sensors in an Ambient Assisted Living (AAL) environment. In particular, the work here presented adopts a new 3D Qualitative Trajectory Calculus (QTC3D) to represent human actions that belong to such activities, designing and implementing a set of computational tools (i.e. Hidden Markov Models) to learn and classify them from standard datasets. Preliminary results show the good performance of our system and its potential application to a large number of scenarios, including mobile robots for AAL.

Additional Information:2015 IEEE/RSJ International Conference on Intelligent Robots and Systems
Keywords:Human-Robot Interaction, Qualitative Spatial Representation, Activities of Daily Living, Ambient Assisted Living
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:18477
Deposited On:27 Aug 2015 04:13

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