By Nathan R. Sturtevant (auth.), Marcelo Kallmann, Kostas Bekris (eds.)
This e-book constitutes the refereed court cases of the fifth foreign Workshop on movement in video games, held in Rennes, France, in November 2012. The 23 revised complete papers offered including nine posters and five prolonged abstracts have been conscientiously reviewed and chosen from various submissions. The papers are prepared in topical sections on making plans, interplay, physics, belief, habit, digital people, locomotion, and movement capture.
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Additional info for Motion in Games: 5th International Conference, MIG 2012, Rennes, France, November 15-17, 2012. Proceedings
Temporal ﬁltering works in realtime with a small delay. We demonstrated the robustness of our system by showing performance animation examples of boxing and table tennis. Similar to most sensor-based performance animation systems, our system may miss the position of 3D motion sensors when a performer moves rapidly. Although we can successfully approximate short-term missed markers using a temporal smoothing function in a postprocess step, markers that are not tracked for a long time cannot be approximated.
Motion data examples of boxing (7,233 frames), table tennis (4,271 frames), and walking motions (1,317 frames) were employed in these experiments. Figure 6 and 7 depict the performance animation results given the performer’s motion of boxing and table tennis,respectively. Both motions are consistently reconstructed using our method. In the boxing example, various types of punches are generated by our method, such as jabs, straight, hooks, and uppercuts. For the table tennis sequence, plausible motions such as forward/backward attacks and side-walking are successfully generated.
For the IO and CIOc algorithms, the number of samples for each target and the camera are set to 25 and 50 respectively (such as in the notation IO-25-50), or 50 and 100 respectively. For CIOc and CIOg , we also show results for the incremental versions of the algorithms (shown with suffix -inc as in CIOc -25-50-inc). The time spent in initialization (a) bars and each application of the behavior rule are presented as well as the average visibility of the targets after 10000 time steps. The results for the bars and islands environments are shown in Table 1.