Human Behaviour Analysis (HBA) is more and more being of interest for Computer Vision and Artificial Intelligence researchers. Its main application areas, like Video Surveillance and Ambient-Assisted Living (AAL), have been in great demand in recent years. This paper provides a review on HBA for AAL and ageing in place purposes focusing specially on vision techniques. First, a clearly defined taxonomy is presented in order to classify the reviewed works, which are consequently presented following a bottom-up abstraction and complexity order. At the motion level, pose and gaze estimation as well as basic human movement recognition are covered. Next, the mainly used action and activity recognition approaches are presented with examples of recent research works. Increasing the degree of semantics and the time interval involved in the HBA, finally the behaviour level is reached. Furthermore, useful tools and datasets are analysed in order to provide help for initiating projects.

In this paper, a human action recognition method is presented in which pose representation is based on the contour points of the human silhouette Weizmann, MuHAVi and IXMAS datasets return high and stable success rates, achieving, to the best of our knowledge, the best rate so far on the MuHAVi Novel Actor test.

Interest in RGB-D devices is increasing due to their low price and the wide range of possible applications that come along. These devices provide a marker-less body pose estimation by means of skeletal data consisting of 3D positions of body joints. These can be further used for pose, gesture or action recognition. In this work, an evolutionary algorithm is used to determine the optimal subset of skeleton joints, taking into account the topological structure of the skeleton, in order to improve the final success rate. The proposed method has been validated using a state-of-the-art RGB action recognition approach, and applying it to the MSR-Action3D dataset. Results show that the proposed algorithm is able to significantly improve the initial recognition rate and to yield similar or better success rates than the state-of-the-art methods.

A review on video-based active and assisted living technologies for automated lifelogging,

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