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We analyse video sequences of a hand interacting with a ball. The hand motion is segmented using a piecewise polynomial motion model inspired by research in motor control. Next, an adaptive gravitational model of the ball is used to locate hand-ball events. We show that hand-ball events can be automatically classified from velocity and acceleration profiles.
When an observer moves in a 3D static scene, the resulting motion field depends on the depth of the visible objects and on the observer's instantaneous translation and rotation. It is well-known that the vector difference - or motion parallax - between nearby image motion field vectors points toward the direction of heading and so computing this vector difference can help in estimating the heading...
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