OpenCollBench - Benchmarking of Collision Detection & Proximity Queries as a Web-Service

We present a server-based benchmark that enables a fair analysis of different collision detection & proximity query algorithms. A simple yet interactive web interface allows both expert and non-expert users to easily evaluate different collision detection algorithms’ performance in standardized or optionally user-definable scenarios and identify possible bottlenecks. In contrast to typically used simple charts or histograms to show the results, we additionally propose a heatmap visualization directly on the benchmarked objects that allows the identification of critical regions on a sub-object level. An anonymous login system, in combination with a server-side scheduling algorithm, guarantees security as well as the reproducibility and comparability of the results. This makes our benchmark useful for end-users who want to choose the optimal collision detection method or optimize their objects with respect to collision detection but also for researchers who want to compare their new algorithms with existing solutions.

[1]  G. Zachmann.  The BoxTree: Exact and Fast Collision Detection of Arbitrary Polyhedra , 1995 .

[2]  Dinesh Manocha,et al.  V-COLLIDE: accelerated collision detection for VRML , 1997, VRML '97.

[3]  Philip M. Hubbard,et al.  Interactive collision detection , 1993, Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium.

[4]  Daniel Cremers,et al.  MOT20: A benchmark for multi object tracking in crowded scenes , 2020, ArXiv.

[5]  Jean-Luc Widlowski,et al.  The RAMI On-line Model Checker (ROMC): A web-based benchmarking facility for canopy reflectance models , 2008 .

[6]  Tomas Akenine-Möller,et al.  A Benchmark for Animated Ray Tracing , 2001, IEEE Computer Graphics and Applications.

[7]  Philip M. Hubbard,et al.  Approximating polyhedra with spheres for time-critical collision detection , 1996, TOGS.

[8]  Michael Manzke,et al.  A framework for benchmarking interactive collision detection , 2009, SCCG.

[9]  Gino van den Bergen.  Efficient Collision Detection of Complex Deformable Models using AABB Trees , 1997, J. Graphics, GPU, & Game Tools.

[10]  Gabriel Zachmann,et al.  SIMDop: SIMD optimized Bounding Volume Hierarchies for Collision Detection , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[11]  René Weller.  A Benchmarking Suite for Static Collision Detection Algorithms , 2007 .

[12]  Dinesh Manocha,et al.  OBBTree: a hierarchical structure for rapid interference detection , 1996, SIGGRAPH.

[13]  C. Preusche,et al.  A benchmarking suite for 6-DOF real time collision response algorithms , 2010, VRST '10.

[14]  Dinesh Manocha,et al.  Rapid and Accurate Contact Determination between Spline Models using ShellTrees , 1998, Comput. Graph. Forum.

[15]  Stefano Caselli,et al.  Exploiting Advanced Collision Detection Libraries in a Probabilistic Motion Planner , 2002, WSCG.

[16]  Dinesh Manocha,et al.  Fast Proximity Queries with Swept Sphere Volumes , 1999 .

[17]  Engin Deniz Diktas,et al.  A Benchmarking Framework for Static Collision Detection , 2008, TPCG.

[18]  Lydia E. Kavraki,et al.  On finding narrow passages with probabilistic roadmap planners , 1998 .

[19]  Ming C. Lin,et al.  CLODs: Dual Hierarchies for Multiresolution Collision Detection , 2003, Symposium on Geometry Processing.

[20]  Guy A. E. Vandenbosch,et al.  SoftLAB, a European web-service for antenna software benchmark , 2009, 2009 3rd European Conference on Antennas and Propagation.

[21]  Gabriel Zachmann,et al.  Rapid collision detection by dynamically aligned DOP-trees , 1998, Proceedings. IEEE 1998 Virtual Reality Annual International Symposium (Cat. No.98CB36180).