Vlasta%20Havran:%20ray%20shooting%20party%20-%20Part%20One.

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Exploiting Temporal Coherence in Ray Casted
Walkthrougs
Vlastimil Havran, Jirí Bittner and Hans-Peter
Seidel
AG4, MPI Informatik, Saarbruecken, Germany
Institute for Computer Graphics, Vienna
University of Technology, Austria
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Talk Outline
Introduction ray shooting and ray casting
temporal coherence New Algorithm Results and
Demo Conclusions and Future Work
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Introduction Ray Shooting
Task Given a ray, find out the first
object intersected.
Input a scene and a ray
Output the object C and
signed distance
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Ray Casting
Image pixel
rays
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Temporal Coherence
Weak Definition a similarity between
subsequent images in the animation.
Exploiting temporal coherence speed up
computation.
Algorithm Categories A static camera, moving
objects B moving camera, static objects
(walkthrough) C moving camera, moving objects
Many coherence classes exist. ray coherence,
spatial coherence, temporal coherence, traversal
coherence, etc. (see Eduard Groellers PhD
thesis, TU Vienna)
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Previous and Related Work
Glassner, 88 Spacetime ray tracing for
animation. Badt Jr, 88 Two algorithms for taking
advantage of temporal coherence in ray
tracing. Groeller and Purgathofer, 91 Using
Temporal and spatial coherence for
acceleration of animation sequences. Sudarsky,
93 Exploiting Temporal Coherence in
Animation Rendering. A Survey. Adelson, 95
Generating exact-raytraced animation frames
by reprojection. Walter et al., 99 Interactive
rendering using Render Cache,
EGWR99. Reinhard et al., 01 Parallel Point
Reprojection. Lin. Q et al., 00 Frame Coherent
Volume Rendering.
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New Algorithm Overview
Main Idea - Compute a single
intersection of the ray with an object, if
possible - If not possible -gt ordinary ray
shooting algorithm First frame use ordinary
ray shooting, remember
intersection points in 3D space Next frames
reproject points, check if we can
decide on intersection objects
Properties intersection points and
surface normals compute correctly (unlike
in RenderCache etc.)
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New Algorithm Data Structures
POS array in 2D point in 3D, object ID,
distance (Points in Object Space)
AIP array in 2D object, distance, count
(Auxiliary Image Plane) Size of AIP and POS
width height
First frame use an ordinary ray shooting
algorithm, remember the points
where ray hit objects (store
it to an array POS)
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Reprojection phase
Next frame(s) using reprojection for each
pixel (xx,yy) do reproject a point
(POS(xx,yy)) from previous frame to AIP at pixel
(x,y), compute approximate distance tp. for
each reprojected point from POS store distance tp
into neighbourhood 3x3 of (x,y) at AIP. Overwrite
farther already stored points by closer ones. If
the reprojected points are from the same object,
increment AIP(X,Y).count, for all 9 pixels
Xx-1,x,x1, Yy-1,y,y1. end-for
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Ray Casting based on Reprojection
Next frame(s) ray casting for each pixel
(x,y) (x0...width), (y0...height) do if
AIP(x,y).count gt THRESHOLD then
ray-cast ray(x,y) to AIP(x,y).OBJ end-if
if (intersection was not found) then
use an ordinary ray shooting algorithm.
end-if end-for THRESHOLD
5, 6, 7, 8, or 9
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Dilatation of Objects (footprint)
Properties reprojection using 3x3 neighbourhood
corresponds to dilatation on the image plane.
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Scene Example
RED - reprojection successfull
GREEN - reprojection fails
WHITE - regular
resampling
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Reprojection Failures
Question When reprojection cannot be used
? Answer appearance of new objects occluding
previously visible objects a)
that were outside viewing frustum (view
frustum errorr) b) that were occluded
(occlusion error) c) that were too small
(undersampling error)
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View Frustum Error
Moving backward.
View Frustum Error
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Occlusion Error
Occluded objects that appear.
Occlusion Error
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Solution to Occlusion Error Epipolar Geometry
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Correct Reprojection Algorithm
Check possible occlusion on the fly.
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Small Approaching Objects
Problem Let us have a scene with polygon A that
in reprojection has big footprint. Some small
objects of current subpixel size are placed in
front of A and are not currently
visible. Question What happens when we enclose
the polygon and use only and only the
reprojection ?
Answer Small objects are missing!
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Resampling Order
maximize the probability that small object of
subpixel size will be detected when moving
camera straight forward.
Goal minimize discrepancy of resampling
pattern in spatio-temporal domain
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Further Improvements
Shifting Ray Origin - when reprojection fails, we
can move the ray origin along the ray path to
avoid traversing empty space. Handling
background - sphere enclosing the whole scene,
use as any other object (always
overwritten). Double Reprojection - edges
between connected objects in 3D must be
recomputed. Use two AIP arrays, keep two closest
objects information. Collision detection -
between camera and the environments based on
signed distance is quite simple to implement.
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Note on Reprojection Efficiency
How many arithmetical operations to reproject
one point from 3D space to image plane ?
8x (), 3x (-), 12x (multiplication), 1x
(division), 1xSQRT, and 2xIF.
Note Image-based incremental reprojection
techniques by McMillan and Mark are not
applicable, since we need signed distance!
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Walkthrough Demo
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Results HW independent profiling
ORSA ordinary ray shooting algorithm REPR ray
casting with reprojection IRSA ideal ray
shooting algorithm
N_IT
FPS
N_TS
T_REN
ORSA 9.23 52.0 701 sec 1.17
Scene A, 85k objects, 825 frames
REPR 3.37 12.2 478 sec 1.72
IRSA 0.98 0.0 256 sec 3.22
ORSA 3.02 44.5 892 sec 1.65
Scene B, 626k objects, 1489 frames
REPR 1.89 21.9 789 sec 1.89
IRSA 0.98 0.0 355 sec 4.19
ORSA 3.79 58.1 979 sec 1.19
Scene C, 112k objects, 1165 frames
REPR 2.73 26.0 838 sec 1.39
IRSA 0.999 0.0 374 sec 3.11
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Results Summary
tested on three different scenes. increased
speedup (with shading, 512x512) scene A
1.17 fps to 1.72 fps (85x103 objects) scene B
1.65 fps to 1.89 fps (626x103 objects)
scene C 1.19 fps to 1.39 fps (112x103
objects) 11.1 pixels computed by regular
resampling 78.9 pixels computed by
reprojection 10 pixels computed by ordinary
ray shooting algorithm
Question is this interesting and valuable
speedup ?
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Results Profiling (scene A)

ORSA
REPR IRSA
RayShooting Function 63.4 25.5
18.7
Compute Color 28.7 41.4
63.6 281 sec
Ray Initialization 1.1 1.7
2.9
Extra ray-object inters. ------ 3.2
------
Reprojection phase ------ 14.7
------
Rest of Computation 6.7 13.5
15.3
Profiler timing sec 1001 676
442
REPR/ORSA Visibility speedup 1.81 (45
savings in time) IRSA/ORSA Visibility speedup
4.44 (77 savings in time) !!!
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Conclusions
conservative ray casting algorithm based on
temporal coherence using reprojection aimed at
solving hidden surface removal (visibility).
(previous algorithms based on reprojection
interpolate colour information from 3D space).
possible use in online mode (many reprojection
techniques for ray-casting/tracing are
offline). good use of temporal coherence, where
temporal coherence exists (80 pixels computed by
single ray-object intersection).
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Future Work
use in context of global illumination
methods. generalisation to scenes with moving
objects. instead of using objects ID, use a
pointer to the cells of spatial subdivision,
thus decreasing the dependency on visual
complexity. extension to visibility for direct
illumination is possible (point light source
exactly and area light
sources with good quality).
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