A critical examination of Allen's theory of action and time
Artificial Intelligence
Neural Computation
Model structure and reliable inference
Perception as Bayesian inference
The computational perception of scene dynamics
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
Trajectory Segmentation Using Dynamic Programming
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
The computational perception of scene dynamics
The computational perception of scene dynamics
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Robust online appearance models for visual tracking
Robust online appearance models for visual tracking
Grounding the lexical semantics of verbs in visual perception using force dynamics and event logic
Journal of Artificial Intelligence Research
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We segment the trajectory of a moving object into piece-wise smooth motion intervals separated by motion boundaries . Motion boundaries are classified into various types, including starts, stops, pauses, and discontinuous changes of motion due to force impulses. We localize and classify motion boundaries by fitting a mixture of two polynomials near the boundary. Given a classification of motion boundaries, we use naive physical rules to infer a set of changing contact relationships which explain the observed motion. We show segmentation and classification results for several image sequences of a basketball undergoing gravitational and nongravitational motion.