Computer understanding of human actions from video has gained recognition as a challenging research area with applications in human-computer interaction, coding, animation and surveillance.
In this talk I will discuss computational approaches for modeling, estimation and recognition of deformable and articulated motions in video sequences. I will demonstrate the application of these models to the analysis of human face expressions and articulated movement. The motion models will explore the following dimensions:
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Instantaneous versus temporal formulations
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General models versus learned movement-specific models
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Stationary versus moving camera
I will initially propose models for instantaneous motion estimation based on spatial constraints. Then, I will define the concept of spatio-temporal motion trajectories of brightness in image sequences, formalize learning and estimation of movement trajectories and demonstrate its use in tracking and interpreting human motion as observed from stationary and moving cameras. Finally, I will discuss future research directions and challenges that lie ahead.