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Human behaviour recognition plays a significant role in early intervention for the cognitive rehabilitation of older people. While existing methods focus on improving third-person vision, human visual attention has been largely ignored in ...

This talk aims to argue for a fine(r)-grained perspective onto human-object interactions. Motivation: Observe a person chopping some parsley. Can you detect the moment at which the parsley was first chopped? Whether the parsley was chopped coarsely or ...

We consider the problem of localizing visitors in a cultural site from egocentric (first-person) images. Localization information can be useful both to assist the user during his visit (e.g., by suggesting where to go and what to see next) and to ...

Wearable cameras, which are becoming common mobile sensing platforms to capture the environment surrounding a person, can also be used to infer activities of the wearer. In this paper we critically discuss features for ego-centric activity recognition ...

The authors propose a method to improve activity recognition by including the contextual information from first person vision (FPV). Adding the context, i.e. objects seen while performing an activity, increases the activity recognition precision. This is ...

Clothing conveys a strong communicative message in terms of social signals, influencing the impression and behaviour of others towards a person; unfortunately, the nature of this message is not completely clear, and social signal processing approaches ...

Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center. They often create discomfort with marker suits, and their recording volume is ...

A wearable gaze tracking device can work with users in daily-life. For long time of use, a non-active method that does not employ an infrared illumination system is desirable from safety standpoint. It is well known that the eye model constraints ...

We propose a method of predicting human egocentric visual attention using bottom-up visual saliency and egomotion information. Computational models of visual saliency are often employed to predict human attention; however, its mechanism and ...