The time varying human multijoint arm dynamics can be modeled by two factors, simplified musculoskeletal dynamics and the uncertainty factor consisting of measurement noises and m...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
Recognition of motions and activities of objects in videos requires effective representations for analysis and matching of motion trajectories. In this paper, we introduce a new r...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
This paper presents a unified approach to human activity capturing and recognition. It targets applications such as a speaker walking, turning around, sitting and getting up from ...