XFastMesh Fast View-dependent Meshing from External Memory - PowerPoint PPT Presentation

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XFastMesh Fast View-dependent Meshing from External Memory

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Each half-edge stores its reverse half-edge, and starting vertex ... Given block ID, lookup disk address in block index, read from disk ... – PowerPoint PPT presentation

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Title: XFastMesh Fast View-dependent Meshing from External Memory


1
XFastMeshFast View-dependent Meshing from
External Memory
Christopher DeCoro Renato B. Pajarola
cdecoro_at_cat.nyu.edu http//www.cat.nyu.edu/cdecor
o/ Center for Advanced Technology Courant
Institute of Mathematical Sciences New York
University pajarola_at_ics.uci.edu http//www.ics.uc
i.edu/graphics/ Computer Graphics Lab Dept. of
Information Computer Science University of
California Irvine
2
Talk Outline
  • Introduction
  • Motivation and applications
  • Related work
  • Background
  • External-memory structure
  • Main-memory structure
  • Experimental results
  • Future work

3
Motivation
  • Huge geometric models
  • Digital 3D scanners
  • Digital Michelangelo's David, 8M triangles
  • CAD, scientific visualization, GIS
  • Limited rendering performance
  • Graphics hardware accelerators can render a fixed
    amount of triangles in real-time
  • We can acquire huge models that far exceed the
    capability of graphics cards in the foreseeable
    future
  • Limited memory size
  • Current models can require more storage than we
    can afford to spend (or want to spend)
  • Multiresolution formats require additional space

4
Related Work
  • View-dependent mesh simplification
  • binary vertex trees Xia et al. 96 and Hoppe
    97
  • multi-triangulation DeFloriani et a. 98
  • vertex clustering hierarchies Luebke Erikson
    97 and Schmalstieg Schaufler 97
  • FastMesh Pajarola 01
  • External-memory mesh simplification
  • El-Sana and Chiang 2001
  • Prince 2000

5
Background - Half-edges
B
B
A
Edge collapse
A
b
b
a
a
h.n.v
h
h
h.v
Vertex split
c
d
d
D
D
c
C
C
  • Represents mesh and simplification operations
    with half-edges and edge collapses / vertex
    splits
  • Three consecutive half-edges form a triangle
  • Each half-edge stores its reverse half-edge, and
    starting vertex
  • Half-edges allow for efficient local mesh update
  • Each vertex split introduces 1 vertex and 2
    triangle faces

6
Background -Multiresolution Hierarchy
expanded vertex splits
collapsed edges and faces
Half-edge collapse hierarchy
  • Uses a hierarchy of half-edge-collapse operations
  • Each node corresponds to a split/collapse
  • Level of detail represented as front through
    hierarchy
  • Detail increases as the front descends the tree

7
Background - Basic Simplification Criteria
  • Out-of-frustum Simplification
  • Back-face Simplification

8
Background Heuristic Simplification Criteria
  • Screen-projection Simplification
  • Normal-angle Deviation
  • Silhouette Preservation

9
Background - LOD parameters
  • Bounding spheres
  • minimal sphere enclosing all affected triangles
    (vertices) and spheres of child nodes

10
Background - LOD parameters
  • Bounding spheres
  • minimal sphere enclosing all affected triangles
    (vertices) and spheres of child nodes
  • Bounding normal cones
  • minimal bounding cone around vertex normal
    enclosing all normal directions of subtree

11
Talk Outline
  • Introduction
  • External-memory structure
  • Overview
  • Initial mesh
  • Detail blocks
  • Auxiliary data
  • Data file construction
  • Main-memory structure
  • Experimental results
  • Future work

12
External Memory Structure Overview
  • Base mesh stored as-is in external storage
  • Loaded at run-time, kept resident during
    execution
  • Detail stored as discrete blocks
  • Similar in structure to a B-tree (high-degree
    nodes)
  • Links within a block represented implicitly
  • All faces/vertices/half-edges given unique ID
  • ID is used to determine the block number
  • Block number is used to determine disk location

13
Detail blocks
  • Edge-collapse trees are divided into blocks
  • Assumes full subtrees
  • Forms block tree
  • High-degree nodes, similar to B-tree
  • Blocks efficiently encode detail
  • Intra-block links represented implicitly

14
Detail blocks Geometry
  • Form disc-like regions on the surface
  • Therefore, block nodes are located spatially
    close together
  • Similar positions and orientation
  • Lower level blocks form smaller disks
  • Parent discs (left) encompass child discs (right)

15
Detail Blocks - Contents
  • Information is stored for each existing node
  • Vertex, normal coordinates
  • Bounding sphere radius, bounding cone angle
  • Global ordering
  • Used for fold-over prevention
  • Four Adjacent half-edges
  • Connectivity used to place new edges into mesh
  • Stores connectivity to other blocks
  • ID of parent node (locates block and node)
  • ID of all child nodes
  • Flags
  • Indicates number of nodes present

16
Detail Blocks - Packing
  • High-degree trees will have many leaves
  • As blocks store complete subtrees, leaf blocks
    will be non-full
  • Leaf blocks do not need child pointers
  • Blocks are packed to remove wasted space
  • Only nodes that exist are stored in block
  • Flags indicate which blocks are available
  • Maintains complete subtree structure
  • Child pointers stored only for non-leaf nodes
  • Also indicated by flag

17
Auxiliary Data
  • Header
  • Fixed sized header indicating locations of other
    fields
  • Initial Mesh
  • Base mesh M0 stored explicitly on disk, loaded at
    start time
  • Block Index
  • For given block b, stores disk offset of b
  • Required because packing scheme results in blocks
    with varying sizes
  • Index itself can be entirely loaded at startup,
    or accessed through memory-mapping
  • Root Block List
  • Lists which blocks contain root nodes of the
    hierarchy
  • Root blocks are loaded at start time and kept
    resident

18
Talk Outline
  • Introduction
  • External-memory structure
  • Main-memory structure
  • Overview
  • Block loading
  • Block deletion
  • Experimental results
  • Future work

19
Main-memory Structure - Overview
  • Block Directory
  • Points to all loaded blocks
  • Similar to a page table
  • High bits of ID represent block
  • Low bits of ID represents offset in block
  • Time Priority Queue
  • Min-queue that stores blocks by least recently
    used
  • Used for caching blocks

20
Tree Node
  • Mesh
  • Stores additional vertex, normal coordinates
  • Six half-edges, representing two faces introduced
    by split
  • Trees
  • Links to merge tree nodes
  • Links to block tree nodes
  • Timestamp
  • Simplification parameters

21
Block Loading
  • Case 1 Front moves below frontier of loaded
    blocks
  • Frontier lowest point in the hierarchy for which
    blocks are loaded
  • Given block ID, lookup disk address in block
    index, read from disk
  • Inflate block from disk format enter into
    directory, attach to tree

22
Block Loading
  • Case 2 Forced split requires load of arbitrary
    block
  • Update operations that can be required to
    maintain mesh
  • results from edge collapses
  • From split edge ID, determine block ID read
    block
  • Use parent ID to load parent block
  • Repeat until all blocks are connected into the
    hierarchy

23
Block Deletion
  • Caching is required for acceptable performance
  • Once user-specified quota is reached, blocks will
    be deleted
  • Least-recently-used blocks are removed first
  • Marked as unused when front moves above root node
    of block
  • Maintains a priority-queue to determine LRU blocks

24
Talk outline
  • Introduction
  • External-memory structure
  • Main-memory structure
  • Experimental results
  • Storage cost
  • Run-time performance
  • Examples
  • Future work

25
Storage cost
  • Cost of data file measured on disk
  • Less than 30 bytes/tri
  • Compares to our original format (about equal)
  • More efficient than previous external methods

26
Run-time performance
Sun 450MHz UltraSPARC-II CPU, Expert3D PCI
graphics
  • Results shown are average time per frame
  • Block load time is generally dominated by
    rendering
  • Block load time also tends to be much less than
    the view-dependent operations
  • Through caching, load time tends to decrease as a
    percentage of frame over time

27
More examples
  • Upper row displays view from users perspective
  • Lower row shows same image from outside view
    (represented as yellow pyramid)
  • Threshold adjusted to achieve constant 5 frames /
    second
  • Between 50 K 67 K triangles per frame

28
Animated example
29
Future work
  • Out-of-core Preprocess
  • Would allow more flexibility in creating models
  • Asynchronous disk access
  • Parrallelize time spent reading from disk
  • Pre-fetch
  • One solution could be based on predicting path of
    camera movement
  • Another could base prefetching based on rate of
    change in the front
  • Geometry Compression
  • Allows more information transferred through disk
    bottleneck
  • Tradeoff between processor speed vs. disk
    speed/storage

30
Conclusion
  • Straight-forward approach to external-memory
    meshing can be successful, if implemented
    efficiently
  • Hierarchy broken into blocks
  • Minimal transformations to hierarchy required
  • Synchronous disk access
  • Disk access overhead, when blocks are cached, can
    be minimized
  • Synchronous access does not present excessive
    overhead
  • History-based Caching
  • Least-recently used caching scheme dramatically
    reduces disk accesses
  • No need to attempt prediction of detail required
    in upcoming frames
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