Monszpart, A;
Thuerey, N;
Mitra, NJ;
(2016)
SMASH: Data-driven Reconstruction of Physically Valid Collisions.
CM Transactions on Graphics (TOG)
, 35
(6)
, Article 199. 10.1145/2980179.2982421.
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Abstract
Collision sequences are commonly used in games and entertainment to add drama and excitement. Authoring even two body collisions in real world can be difficult as one has to get timing and the object trajectories to be correctly synchronized. After trial-anderror iterations, when objects can actually be made to collide, then they are difficult to acquire in 3D. In contrast, synthetically generating plausible collisions is difficult as it requires adjusting different collision parameters (e.g., object mass ratio, coefficient of restitution, etc.) and appropriate initial parameters. We present SMASH to directly ‘read off’ appropriate collision parameters simply based on input video recordings. Specifically, we describe how to use laws of rigid body collision to regularize the problem of lifting 2D annotated poses to 3D reconstruction of collision sequences. The reconstructed sequences can then be modified and combined to easily author novel and plausible collision sequences. We demonstrate the system on various complex collision sequences.
Type: | Article |
---|---|
Title: | SMASH: Data-driven Reconstruction of Physically Valid Collisions. |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1145/2980179.2982421 |
Publisher version: | https://doi.org/10.1145/2980179.2982421 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Graphics; Computer Vision and Pattern Recognition; 3D reconstruction, rigid body collision, optimization |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/1497094 |
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