@inproceedings{5927488d4c7c44c3be66de3a74bad2fc, title = "GPCD: Grid-based predictive collision detection for large-scale environments in computer games", abstract = "Given a time horizon parameter h and an object set O, predictive collision detection finds all the object pairs 〈 oi, oj, t i 〉 which will collide in the future time interval [t, t + h] (where 1 ≤ i, j ≤ n, ti ∈ [t, t + h]). Although there are a number of state-of-the-art approaches to solve collision detection problems, predictive collision detection is addressed for the first time. In this paper, we propose a grid-based predictive collision detection algorithm (GPCD), which is a general technique for the efficient detection of the collision of object pairs in a future time interval. GPCD first determines a candidate list which stores the object pairs having a non-zero probability to collide in a future time. Then, GPCD achieves low running time based on two pruning strategies: (i) space intersection test and (ii) time intersection test. These two pruning strategies eliminate most of the false collision cases in an initial filtering phase. In the refinement phase, a bounding-volume tree is applied to refine the detection results. Our experiments show that GPCD works well for the purpose of predictive collision detection. {\textcopyright} 2006 IEEE.", author = "Zhiwen Yu and Hau-San Wong", year = "2006", doi = "10.1109/ICME.2006.262708", language = "English", isbn = "1424403677", volume = "2006", pages = "1025--1028", booktitle = "2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings", note = "2006 IEEE International Conference on Multimedia and Expo, ICME 2006 ; Conference date: 09-07-2006 Through 12-07-2006", }