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Minimizing probable collision pairs searched in interactive animation authoring

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Abstract

Animation authoring involves an author’s interaction with a scene, resulting in varying scene complexity for a given animation sequence. In such a varying environment, detection and prediction of collision in minimal time and with high accuracy is a challenge. This paper proposes using the bounding volume-based space subdivision mechanism to reduce search space for an object pair collision search. This data structure is enhanced using a direction-based spatial hash table, which predicts collision between static and dynamic objects. These techniques are shown to work in conjunction with existing search space reduction methods. The event of collision is accurately detected using known methods, such as kinetic data structures. Simulation results show that for a scene with 10000 objects with varying dynamic objects (10–90%), the method finds probable collision-pairs with 95–99% accuracy.

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Authors and Affiliations

  1. Department of Computer Science, The University of Texas at Dallas MS EC 31, PO Box 830688, Richardson, TX, 75083, USA

    Parag Agarwal, Srinivas Rajagopalan & B. Prabhakaran

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  1. Parag Agarwal
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  2. Srinivas Rajagopalan
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  3. B. Prabhakaran
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Correspondence to Parag Agarwal.

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Agarwal, P., Rajagopalan, S. & Prabhakaran, B. Minimizing probable collision pairs searched in interactive animation authoring. Visual Comput 24, 347–359 (2008). https://doi.org/10.1007/s00371-007-0193-9

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