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Ray Tracing Animated Scenes using Motion Decomposition Johannes Günther, Heiko Friedrich, Ingo Wald, Hans-Peter Seidel, and Philipp Slusallek.

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Presentation on theme: "Ray Tracing Animated Scenes using Motion Decomposition Johannes Günther, Heiko Friedrich, Ingo Wald, Hans-Peter Seidel, and Philipp Slusallek."— Presentation transcript:

1 Ray Tracing Animated Scenes using Motion Decomposition Johannes Günther, Heiko Friedrich, Ingo Wald, Hans-Peter Seidel, and Philipp Slusallek

2 September 7, 2006Eurographics, Vienna2 Introduction  Nowadays realtime ray tracing on single PC –Packet tracing [Wald PhD04, Reshetov SIG05 ] –Clever acceleration structures (SAH [McDonald GI89 ] )  Best known method: kd-trees [Havran PhD01 ]  BUT, so far only static scenes –Walkthrough –Rigid-body animations [Wald PVG03 ]  Reason: high kd-tree build time  preprocessing

3 September 7, 2006Eurographics, Vienna3 Related Work – Dynamic Scenes Three approaches:  Alternative acceleration structures –BVHs [Wald TOG06, Lauterbach RT06] –Grids [Wald SIG06] –Hybrid data structures [Woop GH06, Havran RT06, Wächter EGSR06]  Faster construction of kd-trees –[Popov RT06, Hunt RT06]  Avoid the (re)construction of kd-trees

4 September 7, 2006Eurographics, Vienna4 Avoid Updating the KD-Tree  IDEA: “make dynamic scenes static”  Assumptions: –Deformation of a base mesh (constant connectivity) –All frames of animation known in advance –Local coherent motion

5 September 7, 2006Eurographics, Vienna5 Method Overview  Motion decomposition –Affine transformations + residual motion  Fuzzy kd-tree –Handles residual motion  Clustering –Exploit local coherent motion

6 September 7, 2006Eurographics, Vienna6 Motion Decomposition  Dynamic scene: ball thrown onto floor

7 September 7, 2006Eurographics, Vienna7 Motion Decomposition  Affine transformations –Approximate deformations –Include shearing (3 rd frame)

8 September 7, 2006Eurographics, Vienna8 Motion Decomposition residual motion

9 September 7, 2006Eurographics, Vienna9 Motion Decomposition fuzzy boxes

10 September 7, 2006Eurographics, Vienna10 Fuzzy KD-Tree  Handles residual motion  KD-Tree over the fuzzy boxes of triangles  Valid over complete animation

11 September 7, 2006Eurographics, Vienna11 Illustration transformation

12 September 7, 2006Eurographics, Vienna12 Illustration affine transformations onlyadding residual motion

13 September 7, 2006Eurographics, Vienna13 Details: Clustering  Efficient ray tracing: –Small fuzzy boxes  Minimize residual motion  Cluster coherently moving triangles  Many clustering algorithms –But mostly for static meshes –Not designed for ray tracing  Develop new one –based on Lloyd relaxation

14 September 7, 2006Eurographics, Vienna14 Clustering Algorithm  Start with one cluster (all triangles)  Lloyd relaxation: –Find transformations for clusters  Linear least squares problem –Recluster triangles –Until convergence  Insert new cluster –Seeded by triangle with highest residual motion  Until improvement below threshold

15 September 7, 2006Eurographics, Vienna15 Ray Tracing: Two-level Approach  Build top-level kd-tree over current cluster bounds  Transform rays into local coordinate system –Inverse affine transformation of cluster from motion decomposition  Traverse fuzzy kd-tree of cluster

16 September 7, 2006Eurographics, Vienna16 Results

17 September 7, 2006Eurographics, Vienna17 Video

18 September 7, 2006Eurographics, Vienna18 Ray Tracing Performance Single CPU (Opteron 2.8 GHz) 1024×1024 px Incl. shading

19 September 7, 2006Eurographics, Vienna19 More Complex Shading  With texturing, lighting, shadows: 2.2 fps (static kd-tree: 4.1 fps)

20 September 7, 2006Eurographics, Vienna20 Comparison to Static KD-Tree  Baseline: separate static kd-tree per frame  Traversal steps –Factor 1.5 - 2  Intersections –Factor 1.2 – 2, Cow 4, Chicken 6  Average fps –Factor 1.2 – 2.6, alone two-level kd-tree costs ca. 30%  Memory –only one fuzzy kd-tree (+ transformation matrices) –vs. #frames static kd-trees

21 September 7, 2006Eurographics, Vienna21 Clustering Process Residual Motion

22 September 7, 2006Eurographics, Vienna22  Clustering also in time domain –Better adaptation to separated animation sequences –E.g. with the chicken: walking, being scared, flying  Handle interpolation between key frames –By interpolation of the computed transformations?  Interaction with dynamic scenes –So far all poses known in advance  Harnessing more information from application –Skinning operators, skeleton, joint angles with limits –See also [TVC/PG06] Future Work

23 September 7, 2006Eurographics, Vienna23 Summary  Animated scenes at interactive frame rates –Motion decomposition and fuzzy kd-trees  Automatic clustering into coherently moving sub-meshes  Integrates nicely into existing ray tracing systems

24 September 7, 2006Eurographics, Vienna24 Questions? Thank You

25 September 7, 2006Eurographics, Vienna25

26 September 7, 2006Eurographics, Vienna26  Transformation X of vertex v  Solve linear least squares problem Finding “Good” Transformations

27 September 7, 2006Eurographics, Vienna27 Clustering Process Residual MotionSurface Area


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