Deferred Splatting. Gaël GUENNEBAUD Loïc BARTHE Mathias PAULIN IRIT UPS CNRS TOULOUSE FRANCE.

Transcription

1 Deferred Splatting Gaël GUENNEBAUD Loïc BARTHE Mathias PAULIN IRIT UPS CNRS TOULOUSE FRANCE

2 Plan Complex Scenes: Triangles or Points? High Quality Splatting: Really efficient? Deferred Splatting: Accurate point selection Temporal Coherency Applications: Occlusion culling & SPT Results Future Works

3 Motivations Real Time rendering of Complex Scenes Triangles: fully supported by graphics HW, but... tiny triangles are inefficient multi resolution can be very tedious One solution is Points: no connectivity, no texture map, no... multi resolution rendering: simple & efficient but...

4 Motivations One solution is Points, but... Large magnification: low quality Flat surfaces: inefficiency hybrid, triangles and points are complementary: use triangles when points become less efficient High Quality point rendering is expensive deferred splatting! IRIT University of Toulouse France

5 Efficient Point Rendering 2 issues: How to select points that have to be rendered? How to render the points?

6 Efficient Point Rendering How to select points that have to be rendered? Store points into a hierarchical data structure (kd tree, octree, hierarchy of bounded spheres,...) Recursive traversal with visibility culling (view frustum,back face,occlusion,...) LOD selection (local density estimation, remove superfluous points) How to render the points?

7 Efficient Point Rendering How to select points that have to be rendered? How to render the points? Efficiency => graphics HW splatting approach

8 GPU Point Rendering quality & performance issues Standard GL_POINTS ( render a disk instead of a square is almost free ) Opaque ellipses High Quality Splatting ( accumulation of elliptic Gaussian, e.g. EWA Surface Splatting ) Number of million of points per second (GeForceFX 5900 under Linux) vs 44 M of small triangles per second

9 Complex Scenes : Example Scene ~ 6800 trees 1 tree ~ 750k points 5000 Millions points After High Level culling & LOD: ~ 4 M points are still potentially visible and have to be rendered But in fact only 150k are really visible!

10 Our Solution : Deferred Splatting is similar to deferred shading : Defer expensive rendering computations to visible points only is based on: An accurate point selection Temporal coherency

11 High Quality Splatting on GPU a multi pass algorithm Hierarchical & multi resolution data structure Data Set GPU High Level Point Selection (Culling, LOD,...) CPU sub set List of selected points (indexes, list of ranges,...) Z buffer buffer

12 High Quality Splatting on GPU a multi pass algorithm Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer CPU In order to accumulate visible splats only: pre compute the depth buffer: std GL_POINTS primitive + per fragment shape & depth correction buffer

13 High Quality Splatting on GPU a multi pass algorithm Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer CPU IRIT University of Toulouse France splatting (2) std GL_POINTS primitive + per fragment Gaussian weight + accumulation buffer

14 High Quality Splatting on GPU a multi pass algorithm Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) CPU sub set Data Set Visibility splatting (1) splatting (2) Owing to : weights 1 GPU Z buffer buffer Normalization (3)

15 High Quality Splatting on GPU [ analyse ] Hierarchical & multi resolution data structure Data Set GPU Visibility splatting (1) High Level Point Selection (Culling, LOD,...) sub set EXPENSIVE / SLOW M pts/s Z buffer COARSE CPU COULD BE HUGE > 4 M pts splatting (2) buffer Normalization (3)

16 The Deferred Splatting Algorithm

17 Accurate Point Selection Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer CPU splatting buffer Normalization

18 Accurate Point Selection Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) CPU sub set Data Set Visibility splatting (1) splatting buffer Normalization GPU Z buffer Break this direct path Add an accurate point selection Only visible points should pass the new test

19 Accurate Point Selection Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer Index (2) Render points as fast as possible: no shading, no blending, no... GL_POINTS, size = 1 pixel = handle of the point CPU = comb(object's id,point's id) IRIT University of Toulouse France buffer = {handle of visible points}

20 Accurate Point Selection Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer Index (2) CPU Read & (2') Sort B i Read the color buffer Extract indices from handles Sort point's indices by object buffer IRIT University of Toulouse France => index arrays B i

21 Accurate Point Selection Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) sub set Data Set Visibility splatting (1) GPU Z buffer Index (2) CPU Read & (2') Sort B i splatting (3) buffer Normalization (4)

22 Accurate Point Selection break this direct path Hierarchical by & taking advantage of Data Set multi resolution temporal coherency data structure High Level Point Selection (Culling, LOD,...) CPU Read & (2') Sort sub set B i Visibility splatting (1) Index (2) splatting (3) GPU Z buffer buffer Normalization (4)

23 Accurate Point Selection Render only points which are Hierarchical visible in the & previous frame multi resolution data structure High Level Point Selection (Culling, LOD,...) CPU Read & (2') Sort B i 1 sub set B i Data Set Visibility splatting (1) B i 1 B i => holes Index (2) splatting (3) GPU Z buffer buffer Normalization (4)

24 Temporal Coherency : Artifacts Frame i Frame i+1 temporal coherency approximation leads to artifacts

25 Temporal Coherency Render only points which are Hierarchical visible in the & previous frame multi resolution data structure High Level Point Selection (Culling, LOD,...) B i 1 sub set Data Set Visibility splatting (1) B Index i 1 B (2) i => holes GPU Z buffer Read & (2') Sort CPU B i splatting (4) buffer Normalization (5)

26 Temporal Coherency Hierarchical & multi resolution data structure Compute B i from the High Level Point Selection (Culling, LOD,...) B i 1 incomplete Z buffer Also compute B i B i 1 sub set Data Set Visibility splatting (1) Update the Index Z buffer (2) : Render B i B i 1 GPU Z buffer Read & (2') Sort CPU B i B i 1 B i Visibility splatting (3) splatting (4) buffer Normalization (5)

27 The Complete Algorithm summary step by step Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) B i 1 Data Set Visibility splatting (1) sub set Index (2) GPU Z buffer Read & (2') Sort CPU B i B i 1 B i Visibility splatting (3) splatting (4) buffer Normalization (5)

28 One point per pixel... Deferred Splatting allows only one point per pixel Advantages Remove superfluous points (LOD selection) Solve color buffer overflow (only 8 bits per component) Drawbacks

29 One point per pixel... Deferred Splatting allows only one point per pixel Advantages Drawbacks We may lose texture information High frequency textured models + coarse high level LOD selection flickering artifacts... Can be solved using surfel mipmap [Pfister et al. 00]

30 Deferred Splatting Applications Occlusion Culling Sequential Point Trees

31 High Level Occlusion Culling Hierarchical & multi resolution data structure High Level Point Selection (Culling, LOD,...) B i 1 Data Set Visibility splatting (1) HW Occlusion Queries (asynchronous) GPU Z buffer Occluded nodes removal sub set buffer CPU

32 Sequential Point Trees [Dachsbacher03] Preprocessing: build a sequential version of the hierarchy

33 Sequential Point Trees [Dachsbacher03] Preprocessing: build a sequential version of the hierarchy Rendering: CPU: fast & coarse selection of a prefix GPU: fine LOD selection at the point level

34 Sequential Point Trees [Dachsbacher03] Preprocessing: build a sequential version of the hierarchy Rendering: CPU: fast & coarse selection of a prefix GPU: fine LOD selection at the point level

35 Sequential Point Trees Preprocessing: build a sequential version of the hierarchy Rendering: CPU: fast & coarse selection of a prefix GPU: fine LOD selection at the point level SPT Coarse SPT selection prefix Classical High Quality Splatting: CPU all points of the coarse prefix are processed by 2 complex vertex programs IRIT University => inefficient of Toulouse France Visibility splatting(1) + SPT fine selection splatting (2) + SPT fine selection GPU

36 Sequential Point Trees Preprocessing: build a sequential version of the hierarchy Rendering: CPU: fast & coarse selection of a prefix GPU: fine LOD selection at the point level SPT Coarse SPT selection prefix Deferred Splatting: CPU all points of the coarse prefix are processed by 1 very simple vertex program IRIT University => efficient of Toulouse France Index (2) + SPT fine selection GPU

37 Results Classical GPU based High Quality Splatting versus Deferred Splatting

38 Results : Simple Head 285k points Average FPS: EWA Splatting: 34 Deferred Splatting: 41 Speed up: x1.2 % of culled points: 50 70% with DS classic IRIT University of Toulouse France EWA Splatting Reading buffer + sort Render Indexes Visibility Splatting

39 Results : 200 Hugo 1 Hugo = 450k points Scene = 200 Hugo in motion Average FPS: EWA Splatting: 11.5 Deferred Splatting: 34.5 Speed up : x3 % of culled points: 90% with DS classic IRIT University of Toulouse France EWA Splatting Reading buffer + sort Render Indexes Visibility Splatting

40 Results : Forest 1 tree = 750k points Scene = 6800 trees Average FPS: EWA Splatting: Deferred Splatting:11 20 Speed up : x10 % of culled points: 90 97% with DS classic with DS classic (1 tree) EWA Splatting Reading buffer + sort Render Indexes Visibility Splatting IRIT University of Toulouse France

41 What about screen resolutions? When the screen size increases The rendering time linearly increases The speed up of deferred splatting remains constant Large resolution => reading the color buffer becomes expensive: 1024² => 25ms! AGP limitation > PCI express? 512x x724 EWA Splatting Reading buffer + sort Render Indexes Visibility Splatting 1024x IRIT University of Toulouse France

42 Usability Unsuitable for simple scenes (< ~300k points) Based on the assumption that a point is visible or not true for small points only (< ~10 pixels) For our initial context it is always true large points are inefficient => use triangles If you don't have a polygonal representation: render large points anyway

43 Conclusion works at the point level and does: view frustum culling occlusion culling (and back face culling) LOD selection high quality splatting on highly complex scenes suitable for dynamic scenes & point clouds no assumption on the high level data structure no additional preprocessing simple and efficient

44 Future Works Full hardware implementation keep the CPU free no slow reading from the GPU to the CPU More efficient/accurate high level point selection new data structures new algorithms IRIT University of Toulouse France

45 Questions?