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A methodology for optimal voxel size computation in collision detection algorithms for virtual reality

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Abstract

Real-time Virtual Reality applications require accuracy but are also time dependent; therefore, in these environments, the time consumption is particularly important. For that reason, when facing the problem of Collision Detection for a Virtual Reality application, we firstly focus our attention on optimizing time performance for collisions among objects. Spatial Partitioning algorithms have been broadly used in Collision Detection. In particular, voxel-based methods are simple and quick, but finding the optimum voxel size is not trivial. We propose a methodology to easily determine the optimal voxel size for Collision Detection algorithms. Using an algorithm which represents volumetric objects with tetrahedra as an example, a performance cost function is defined in order to analytically bound the voxel size that gives the best computation times. This is made by inferring and estimating all the parameters involved. Thus, the cost function is delimited to depend only on geometric data. By doing so, it is possible to determine the optimal voxelization for any algorithm and scenario. Several solutions have been researched and compared. Experimental results with theoretical and real 3D models have validated the methodology. The reliability of our research has also been compared with traditional experimental solutions given by previous works.

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References

  • Biesel D, Gross M (2000) Interactive simulation of surgical cuts. In: Proceedings of the 8th pacific conference on computer graphics and applications, PG ’00. IEEE Computer Society, Washington, DC, USA, pp 116–125

  • Borro D, García-Alonso A, Matey L (2004) Approximation of optimal voxel size for collision detection in maintainability simulations within massive virtual environments. Comput Graph Forum 23:13–24

    Google Scholar 

  • Bradshaw G, O’Sullivan C (2002) Sphere-tree construction using dynamic medial axis approximation. In: 2002 ACM SIGGRAPH/Eurographics symposium on computer animation, SCA ’02. ACM, New York, NY, USA, pp 33–40

  • Brunet P, Navazo I (1990) Solid representation and operation using extended octrees. ACM Trans Graph 9(2):170–197

    Article  MATH  Google Scholar 

  • Fünfzig C, Fellner DW (2003) Easy realignment of k-dop bounding volumes. In: Graphics Interface. A K Peters, Halifax, Nova Scotia, pp 257–264

  • Garcia-Alonso A, Serrano N, Flaquer J (1994) Solving the collision detection problem. IEEE Comput Graph Appl 14:36–43

    Article  Google Scholar 

  • Gissler M, Dornhege C, Nebel B, Teschner M (2009a) Deformable proximity queries and their application in mobile manipulation planning. In: Proceedings of the 5th international symposium on advances in visual computing: Part I, ISVC ’09. Springer, Heidelberg, pp 79–88

  • Gissler M, Schmedding R, Teschner M (2009b) Time-critical collision handling for deformable modeling. Compu Animat Virtual Worlds 20(2–3):355–364

    Google Scholar 

  • Gottschalk S, Lin MC, Manocha D (1996) Obbtree: a hierarchical structure for rapid interference detection. In: ACM Siggraph., volume 30. University of North Carolina, NC, pp 171–180

  • Gregory A, Lin MC, Gottschalk S, Taylor R (2000) Fast and accurate collision detection for haptic interaction using a three degree-of-freedom force-feedback device. Comput Geom 15:69–89

    Article  Google Scholar 

  • Heidelberger B, Teschner M, Gross M (2003) Real-time volumetric intersections of deforming objects. In: VMV’03. Akademische Verlagsgesellschaft Aka GmbH, München, Germany, 461–468

  • Heidelberger B, Teschner M, Keiser R, Müller M, Gross M (2004) Consistent penetration depth estimation for deformable collision response. In VMV’04. Akademische Verlagsgesellschaft Aka, Stanford, USA

  • Hubbard P (1993) Interactive collision detection. In: IEEE 1993 symposium on research frontiers in virtual reality, pp 24–31

  • Klosowski JT, Held M, Mitchell JSB, Sowizral H, Zikan K (1998) Efficient collision detection using bounding volume hierarchies of k-dops. IEEE Trans Vis Comput Graph 4(1):21–36

    Article  Google Scholar 

  • Kockro R, Hwang P (2009) Virtual temporal bone: an interactive 3-dimensional learning aid for cranial base surgery. Neurosurg Clin N Am 64(5 Suppl 2):216–229

    Google Scholar 

  • Kockro RA, Stadie A, Schwandt E, Reisch R, Charalampaki C, Ng I, Yeo TT, Hwang P, Serra L, Perneczky A (2007) A collaborative virtual reality environment for neurosurgical planning and training. Neurosurgery, 61(5 Suppl 2):379–91; discussion 391

  • Larsson T, Akenine-Möller T (2001) Collision detection for continuously deforming bodies. In: Eurographics 2001, short presentations. Eurographics Association, Blackwell Publishing, pp 325–333

  • Lin MC, Gottschalk S (1998) Collision detection between geometric models: A survey. In: Proceedings of IMA conference on mathematics of surfaces, pp 37–56

  • Madera FA, Laycock SD, Day AM (2010) Detecting self-collisions using a hybrid bounding volume algorithm. In: Proceedings of the 2010 third international conference on advances in computer-human interactions, ACHI ’10. IEEE Computer Society, Washington, DC, USA, pp 107–112

  • Malone HR, Syed ON, Downes MS, D’Ambrosio AL, Quest DO, Kaiser MG (2010) Simulation in neurosurgery: a review of computer-based simulation environments and their surgical applications. Neurosurg Clin N Am 67(4):1105–1116

    Article  Google Scholar 

  • McNeely WA, Puterbaugh KD, Troy JJ (1999) Six degree-of-freedom haptic rendering using voxel sampling. In: 26th annual conference on computer graphics and interactive techniques, SIGGRAPH ’99. ACM Press/Addison-Wesley Publishing Co, New York, NY, USA, pp 401–408

  • Melax S (2000) Dynamic plane shifting bsp traversal. In: Graphics Interface. Lawrence Erlbaum Associates, pp 213–220

  • Pascal Volino NMT (2000) Implementing fast cloth simulation with collision response. In: International conference on computer graphics, CGI ’00. IEEE Computer Society, Washington, DC, USA, p 257

  • Schmidl H, Walker N, Lin MC (2004) Cab: Fast update of obb trees for collision detection between articulated bodies. J Grap GPU, and Game Tools 9(2):1–9

    Google Scholar 

  • Smith A, Kitamura Y, Takemura H, Kishino F (1995) A simple and efficient method for accurate collision detection among deformable polyhedral objects in arbitrary motion. In: Proceedings of the virtual reality annual international symposium (VRAIS’95), VRAIS ’95. IEEE Computer Society, Washington, DC, USA, p 136

  • Teschner M, Heidelberger B, Mueller M, Pomeranets D, Gross M (2003) Optimized spatial hashing for collision detection of deformable objects. In: VMV (vision, modeling and visualization). Aka GmbH, Munich, Germany, pp 47–54

  • Teschner M, Kimmerle S, Heidelberger B, Zachmann G, Raghupathi L, Fuhrmann A, Cani M-P, Faure F, Magnenat-Thalmann N, Strasser W, Volino P (2004) Collision detection for deformable objects. In: EUROGRAPHICS, vol 23. pp 119–139

  • van den Bergen G (1997) Efficient collision detection of complex deformable models using aabb trees. J Graph Tools 2(4):1–13

    Article  MATH  Google Scholar 

  • van den Bergen G (2004) Collision Detection in Interactive 3D Environments. Morgan Kaufmann, Los Altos, CA

  • Zachmann G (1998) Rapid collision detection by dynamically aligned dop-trees. In: Proceedings of the virtual reality annual international symposium, VRAIS ’98. IEEE computer society, Washington, DC, USA, p 90

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Acknowledgments

This work has been partially funded by the Government of Navarra within the Plan de Formacion y de Investigacion y Desarrollo program that belongs to the Education department. The authors are also grateful to Prof. Dr. Matthias Teschner (Computer Graphics Laboratory, University of Freiburg, Germany) for his support to carry out the collision detection algorithm, as well as his suggestions and comments on the subsequent study.

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  1. Department of Applied Mechanics, CEIT and Tecnun (University of Navarra), Pamplona, Navarra, Spain

    G. Echegaray & D. Borro

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  1. G. Echegaray
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  2. D. Borro
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Correspondence to G. Echegaray.

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Echegaray, G., Borro, D. A methodology for optimal voxel size computation in collision detection algorithms for virtual reality. Virtual Reality 16, 205–213 (2012). https://doi.org/10.1007/s10055-011-0199-5

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