virtual reality modeling. from (burdea 1996) the vr physical modeling:

Virtual Reality ModelingVirtual Reality Modeling

from (Burdea 1996)

The VR physical modeling:The VR physical modeling:

The Haptics Rendering Pipeline (revisited)The Haptics Rendering Pipeline (revisited)

ForceForce TactileTactileTraversalTraversal DisplayDisplay

ForceForceCalculationCalculation

Force Force SmoothingSmoothing

ForceForceMappingMapping

HapticHapticTexturingTexturing

Collision Collision DetectionDetection

ViewViewTransformTransform

LightingLighting ProjectionProjection TexturingTexturingScene Scene

TraversalTraversal

GeometryGeometry RasterizerRasterizerApplicationApplication DisplayDisplay

adapted from (Popescu, 2001)

The Haptics Rendering PipelineThe Haptics Rendering Pipeline







Uses bounding box collision detection for fast response; Two types of bounding boxes, with fixed size or variable size (depending on enclosed object orientation). Fixed size is computationally faster, but less precise

Collision detection:Collision detection:

Variable size Bounding BoxVariable size Bounding Box Fixed size Bounding BoxFixed size Bounding Box

Collision DetectionCollision Detection

Undetected collisionUndetected collisionBall at timeBall at time t t

Ball at time Ball at time t + 1/fpst + 1/fps

Ball at time tBall at time t

Longest distanceLongest distance

If longest distanceIf longest distance d < v d < v • 1/fps• 1/fpsthen collision is undetected (v is the ball then collision is undetected (v is the ball velocity along its trajectory)velocity along its trajectory)

For more precise detection, we use a two-stage collision detection: an approximate (bounding box ) stage, followed by a slower exact collision detection stage.

Two-stage collision detection:Two-stage collision detection:

Bounding Box PruningBounding Box Pruning multi-body pairsmulti-body pairs

Pair-wise exactPair-wise exactCollision DetectionCollision Detection

Simulation Simulation

Collision responseCollision response

yes

yes

no

Exact collision detectionExact collision detection

Surface cutting: Surface cutting: An extreme case of surface “deformation” is surface cutting. This happens when the contact force exceed a given threshold; When cutting, one vertex gets a co-located twin. Subsequently the twin vertices separate based on spring/damper laws and the cut enlarges.

Cutting instrumentCutting instrumentMesh Mesh beforebefore cut cut Mesh Mesh afterafter cut cut

V2V2V1V1 V2V2V1V1

Collision response – surface deformationCollision response – surface deformation

Haptic Interface PointHaptic Interface Point

Object polygonObject polygon

I -Haptic Interface PointI -Haptic Interface PointHaptic Interface PointHaptic Interface Point

Penetration distancePenetration distance

Haptic interfaceHaptic interface

Force output for homogeneous elastic objectsForce output for homogeneous elastic objects

K K •• d, d, for 0 for 0 d d d d max max

F F maxmax for dfor d max max d d

where where F F maxmax is that haptic interface maximum output force is that haptic interface maximum output force

{{F =F =

F F maxmax

d d max 1max 1 Penetration distance d Penetration distance d d d max 2max 2

Hard objec

t

Hard objec

t

Soft object

Soft object

saturationsaturation

Force Calculation –Force Calculation –Elastic objects with harder interiorElastic objects with harder interior

K K 11 •• d, d, for 0 for 0 d d d d discontinuity discontinuity

K K 1 1 •• d d discontinuity discontinuity + K + K 2 2 •• (d –d (d –d discontinuitydiscontinuity)), , for dfor d discontinuity discontinuity d d

where dwhere d discontinuity discontinuity is object stiffness change point is object stiffness change point

{{F =F =

Penetration distance d Penetration distance d d d discontinuitydiscontinuity

FF

F F rr

F F

Force Calculation –Force Calculation –Virtual pushbuttonVirtual pushbutton

F = K F = K 11 •• d (1-u d (1-umm) +) +

FFrr •• u umm + +

K K 22 •• (d – n) u (d – n) unn

where uwhere umm and u and unn are unit step are unit step

functions at m and nfunctions at m and n

mm nn Penetration distance d Penetration distance d

Virtual wall Virtual wall

FF initial initial = K = K •• d for 0 d for 0 d d

mm

FF = 0 during relaxation,= 0 during relaxation,

F F subsequentsubsequent = K = K 11 •• d d •• u umm for 0 for 0 d d n n

FF = 0 during relaxation,= 0 during relaxation,

where uwhere umm is unit step function at m is unit step function at m

mmmm nn

Force Calculation –Force Calculation –Plastic deformationPlastic deformation

Generate energy due to sampling time-Generate energy due to sampling time-To avoid system instabilities we add aTo avoid system instabilities we add adamping termdamping term

Force Calculation –Force Calculation –Virtual wallVirtual wall

V V 0 0

Virtual wall Virtual wall Moving into the wallMoving into the wall

timetime

F F

V V 0 0

Virtual wall Virtual wall Moving away from the wallMoving away from the wall

timetime

F F

K K wallwall •• x + B v x + B v, , for v for v 0 0

K K wall wall •• x, x, for v for v 0 0

where B is a directional damperwhere B is a directional damper

{{F =F =

where N is the direction of the contact force based on vertex normal interpolation

Force shading: Force shading:

Real cylinder contactReal cylinder contact forcesforces

Non-shaded contactNon-shaded contact forcesforces

Contact forces afterContact forces after shadingshading

K K objectobject •• d d • N• N , , for 0 for 0 d d d d maxmax

F F max max •• N, N, for d for d max max < d< d{{F F smoothedsmoothed = =

The haptic mesh: The haptic mesh: A single HIP is not sufficient to capture the geometry

of fingertip-object contact; The curvature of the fingertip, and the object

deformation need to be realistically modeled.

Screen sequence for squeezing an elastic virtual ballScreen sequence for squeezing an elastic virtual ball

Penetration distance Penetration distance for mesh point for mesh point i

Mesh point Mesh point i

Haptic meshHaptic mesh

Haptic Interface Point Haptic Interface Point iPenetration distance Penetration distance for mesh point for mesh point i

For each haptic interface point of the meshFor each haptic interface point of the mesh::

F F haptic-mesh ihaptic-mesh i = K = K objectobject •• d d mesh imesh i •• N N surfacesurface

where where d d mesh imesh i are the interpenetrating distances at the are the interpenetrating distances at the

mesh points, mesh points, N N surface surface is the weighted surface normal is the weighted surface normal

of the contact polygonof the contact polygon

Haptic mesh force calculationHaptic mesh force calculation







Force Force MappingMapping

Force mappingForce mapping

Force displayed by the Rutgers Master interface: Force displayed by the Rutgers Master interface:

F F displayeddisplayed = ( = ( F F haptic-meshhaptic-mesh ) )•• cos cos

where where it the angle between the mesh force resultant and the piston it the angle between the mesh force resultant and the piston

Tactile mouseTactile mouse

Tactile patterns produced by the Logitech mouseTactile patterns produced by the Logitech mouse

ForceForce

Time Time Time Time Time Time

haptic mouse texture simulation

Surface haptic texture produced by the PHANToM Surface haptic texture produced by the PHANToM interfaceinterface

Haptic interfaceHaptic interface

Haptic Interface PointHaptic Interface Point

Object polygonObject polygon

XX

YY

ZZ

F F texturetexture = A sin(m x) = A sin(m x) •• sin(n y), sin(n y),

where A, m, n are constants:where A, m, n are constants: A gives magnitude of vibrations;A gives magnitude of vibrations; m and n modulate the frequency of m and n modulate the frequency of vibrations in the x and y directionsvibrations in the x and y directions

BEHAVIOR MODELING BEHAVIOR MODELING The simulation level of autonomy (LOA) is a function of its

components Thalmann et al. (2000) distinguish three levels of autonomy. The

simulation components can be either “guided” (lowest),

“programmed” (intermediate” and “autonomous (high) Simulation LOA = f(LOA(Objects),LOA(Agents),LOA(Groups))Simulation LOA = f(LOA(Objects),LOA(Agents),LOA(Groups))

Interactive objectInteractive object Intelligent agentIntelligent agent Group of agentsGroup of agents

Autonomous

Programmed

Guided

Autonomous

Programmed

Guided

Autonomous

Programmed

Guided

Simulation Simulation LOALOA

adapted from (Thalmann et al., 2000)

Interactive objects: Interactive objects: Have behavior independent of user’s input (ex. clock); This is needed in large virtual environments, where it is

impossible for the user to provide all required inputs.

System clockSystem clock

Automatic door – Automatic door – reflex behaviorreflex behavior

Interactive objects: Interactive objects: The fireflies in NVIDIA’s Grove have behavior

independent of user’s input. User controls the virtual

camera;

Agent behavior: Agent behavior: A behavior model composed of perception, emotions,

behavior, and actions; Perception (through virtual sensors) makes the agent

aware of his surroundings.

PerceptionPerception EmotionsEmotions

BehaviorBehavior

ActionsActions

Virtual worldVirtual world

Reflex behavior: Reflex behavior: A direct link between perception and actions (following

behavior rules (“cells”); Does not involve emotions.

PerceptionPerception EmotionsEmotions

BehaviorBehavior

ActionsActions

Object behaviorObject behavior

Another example of reflex behavior – “Dexter” at MIT [Johnson, 1991]: Hand shake, followed by head turn

Autonomous virtual humanAutonomous virtual human

User-controlled hand avatarUser-controlled hand avatar

Agent behavior - Agent behavior - avatarsavatars

If user maps to a full-body avatar, then virtual human agents react through body expression recognition: example dance. Swiss Institute of Technology, 1999(credit Daniel Thalmann)

Autonomous virtual humanAutonomous virtual humanUser-controlled hand avatarUser-controlled hand avatar

Emotional behavior: Emotional behavior: A subjective strong feeling (anger, fear) following perception; Two different agents can have different emotions to the same perception, thus they can have different actions.

Virtual worldVirtual world

Emotions 2Emotions 2 PerceptionPerception

BehaviorBehavior

Actions 2Actions 2

Perception Perception Emotions 1Emotions 1

BehaviorBehavior

Actions 1Actions 1

Crowds behaviorCrowds behavior

(Thalmann et al., 2000)

Crowd behavior emphasizes group (rather than individual) actions; Crowds can have guided LOA, when their behavior is defined explicitly by the user; Or they can have Autonomous LOA with behaviors specified by rules and other complex methods (including memory).

Political demonstrationPolitical demonstration

Guided crowdGuided crowdUser needs to specifyIntermediate path points

Autonomous crowdAutonomous crowdGroup perceives info onits environment and decides a path to follow to reach the goalVC 5.3

MODEL MANAGEMENT MODEL MANAGEMENT It is necessary to maintain interactivity and

constant frame rates when rendering complex

models. Several techniques exist: Level of detail segmentation; Cell segmentation; Off-line computations; Lighting and bump mapping at rendering

stage; Portals.

Level of detail segmentation: Level of detail segmentation: Level of detail (LOD) relates to the number of polygons

on the object’s surface. Even if the object has high

complexity, its detail may not be visible if the object is

too far from the virtual camera (observer).

Tree with 27,000 polygons Tree with 27,000 polygons

Tree with 27,000 polygons Tree with 27,000 polygons (details are not perceived)(details are not perceived)

Static level of detail management: Static level of detail management: Then we should use a simplified version of the object (fewer polygons), when it is far from the camera. There are several approaches: Discrete geometry LOD; Alpha LOD; Geometric morphing (“geo-morph”) LOD.

Discrete Geometry LOD: Discrete Geometry LOD: Uses several discrete models of the same virtual object; Models are switched based on their distance from the

camera (r r0; r0 r r1; r1 r r2; r2 r)

LOD 0LOD 0

LOD 1LOD 1

LOD 2LOD 2

r2 r0

r1

Alpha Blending LOD: Alpha Blending LOD: Discrete LOD have problems on the r0 = r, r1 = r, r2 = r circles, leading to “popping”. Objects appear and disappear suddenly. One solution is distance hystheresis. Another solution is model blending – two models are rendered near the circles; Another solution to popping is alpha blending by changing the transparency of the object. Fully transparent objects are not rendered.

OpaqueOpaque

Less opaqueLess opaque

Fully transparentFully transparent

LOD 0LOD 0

LOD 1LOD 1

LOD 2LOD 2

r2 r0

r1

Hystheresis zoneHystheresis zone

Geometric Morphing LOD: Geometric Morphing LOD: Unlike geometric LOD, which uses several models of the same

object, geometric morphing uses only one complex model. Various LOD are obtained from the base model through mesh

simplification A triangulated polygon mesh: n vertices has 2n faces and 3n edges

Collapsing edgesCollapsing edges

V2V2V1V1

V1V1

Mesh Mesh beforebefore simplification simplification Mesh Mesh afterafter simplification simplification

Single-Object adaptive level of detail LOD: Single-Object adaptive level of detail LOD: Used where there is a single highly complex object that the user wants to inspect (such as in interactive scientific visualization. Static LOD will not work since detail is lost where needed- example the sphere on the right loses shadow sharpness after LOD simplification.

Sphere with 8192 triangles Sphere with 8192 triangles – Uniform high density– Uniform high density

Sphere with 512 triangles – Sphere with 512 triangles – Static LOD simplificationStatic LOD simplification

(from Xia et al, 1997)

Single-object Adaptive Level of DetailSingle-object Adaptive Level of DetailSometimes edge collapse leads to problems, so vertices needto be split again to regain detail where needed. Xia et al. (1997) developed an adaptive algorithm that determines the level of detail based on distance to viewer as well as normal direction (lighting).

V2V2V1V1

Vertex SplitVertex Split

V1V1

Refined MeshRefined Mesh Simplified Mesh Simplified Mesh Edge collapseEdge collapse

V1 is the “parent” vertexV1 is the “parent” vertex

(adapted from Xia et al, 1997)

Single-object Adaptive Level of DetailSingle-object Adaptive Level of Detail

Sphere with 537 triangles Sphere with 537 triangles – adaptive LOD, 0.024 sec – adaptive LOD, 0.024 sec to render (SGI RE2, single to render (SGI RE2, single R10000 workstation)R10000 workstation)

Sphere with 8192 triangles Sphere with 8192 triangles – Uniform high density, – Uniform high density, 0.115 sec to render0.115 sec to render


Single-object Adaptive Level of Detail Single-object Adaptive Level of Detail

Bunny with 3615 triangles Bunny with 3615 triangles – adaptive LOD, 0.110 sec – adaptive LOD, 0.110 sec to render (SGI RE2, single to render (SGI RE2, single R10000 workstation)R10000 workstation)

Bunny with 69,451 Bunny with 69,451 triangles – Uniform high triangles – Uniform high density, 0.420 sec to density, 0.420 sec to renderrender


LOD 1LOD 1

LOD 2LOD 2

Static LOD: Static LOD: Geometric LOD, alpha blending and morphing have problems maintaining a constant frame rate. This happens when new complex objects appear suddenly in the scene (fulcrum).

LOD 1LOD 1

LOD 2LOD 2

frame i frame i+1

Camera “fly-by”Camera “fly-by”fu

lcrum

fulcrum

Architectural “walk-through” Architectural “walk-through” (UC Berkeley Soda Hall)(UC Berkeley Soda Hall)

Camera path through auditorium

No LOD menegament, 72,570 polygonsNo LOD menegament, 72,570 polygons

from (Funkhauser and Sequin, 1993)

A

B

CStartStart

EndEnd

A A C

B

Time 0.2 secTime 0.2 sec

C

B

Time 1.0 secTime 1.0 sec

0 Frames 2500 Frames 250 0 Frames 2500 Frames 250

No LOD management Static LOD management

Adaptive LOD Management-continued: Adaptive LOD Management-continued: An algorithm that selects LOD of visible objects based on a specified frame rate; The algorithm (Funkhauser and Sequin, 1993) is based on a benefits to cost analysis, where cost is the time needed to render Object O at level of detail L, and rendering mode R.

The cost for the whole scene is

where the cost for a single object is

Cost (O,L,R) Cost (O,L,R) Target frame time Target frame time

Cost (O,L,R) = max (c1Polygons(O,L) + c2 Vertices(O,L), c3 Pixels(O,L))Cost (O,L,R) = max (c1Polygons(O,L) + c2 Vertices(O,L), c3 Pixels(O,L))

c1, c2, c3 are experimental constants, depending on R and type of computer c1, c2, c3 are experimental constants, depending on R and type of computer

Adaptive LOD Management: Adaptive LOD Management: Similarly the benefit for a scene is a sum of visible objects benefits;

where the benefit of a given object is

The algorithm tries to maximize each object’s “value”

Objects with higher value (larger size) are rendered first

Benefit(O,L,R)Benefit(O,L,R)

Benefit(O,L,R) = size(O) * Accuracy(O,L,R) * Importance(O) * Focus(O) *Benefit(O,L,R) = size(O) * Accuracy(O,L,R) * Importance(O) * Focus(O) *

Motion(O) * Hysteresis(O,L,R) Motion(O) * Hysteresis(O,L,R)

Value= Benefit(O,L,R)/Cost(O,L,R)Value= Benefit(O,L,R)/Cost(O,L,R)

No detail elision, 72,570 polygonsNo detail elision, 72,570 polygons

Optimization algorithm, 5,300 poly.Optimization algorithm, 5,300 poly. 0.1 sec target frame time (10 fps)0.1 sec target frame time (10 fps)


AC

Level of detail segmentation – rendering modeLevel of detail segmentation – rendering mode

No detail elision, 19,821 polygonsOptimization, 1,389 poly., 0.1 sec target frame time


Level of detail – darkergray means more detail

It is another method of model management,

used in architectural walk-through; To maintain the “virtual building” illusion it

is necessary to have at least 6 fps (Airey et al., 1990) Necessary to maintain interactivity and

constant frame rates when rendering complex

models.

Cell segmentation:Cell segmentation:

Model managementModel managementOnly the current “universe” needs to be rendered

Cell segmentation – increased frame rateCell segmentation – increased frame rate

Automatic floor plan partition (Airey et al., 1990)

Buildings are large models that can be partitioned in “cells”automatically and off-line to speed up simulations at run time; Cells approximate rooms; Partitioning algorithms use a “priority” factor that favors occlusions (partitioning along walls)

Cell segmentation Cell segmentation

From (Funkhauser, 1993)

Building model resides in a fully associative cache; But cell segmentation alone will not work if the model is so large that it exceeds available RAM; In this case large delays will occur when there is a page fault anddata has to be retrieved from hard disk;

Page faultsPage faults

Fra

me

tim

e (s

)F

ram

e ti

me

(s)

FramesFrames

Combined Cell, LOD and database Combined Cell, LOD and database methodsmethods

Floor plan partition (Funkhouser, 1993)

UserUser

InterfaceInterface

VisibilityVisibility

Determ.Determ.

DetailDetail

EllisionEllision RenderRender MonitorMonitor

Look-Look-ahead ahead Determ.Determ.

Cache Cache Manage-Manage-mentment

I/O I/O OperOper

DatabaseDatabase

Database managementDatabase management

It is possible to add database management techniques to preventpage faults and improve fps uniformity during walk-through; It is possible to estimate how far the virtual camera will rotate andtranslate over the next N frames and pre-fetch from the hard disk theappropriate objects.

Database managementDatabase management

LOD 1LOD 1

LOD 0LOD 0

LOD 3LOD 3

LOD 2LOD 2LOD 1LOD 1

LOD 0LOD 0

LOD 2LOD 2

LOD 1LOD 1

LOD 0LOD 0LOD 0LOD 0

Fra

me

tim

e (s

)F

ram

e ti

me

(s)

FramesFrames

Floor plan visibility and highest LOD (Funkhouser, 1990)

LOD 0 – lowest level of detail (loaded first)LOD 0 – lowest level of detail (loaded first)……..LOD 3 - highest level of detail (loaded last)LOD 3 - highest level of detail (loaded last)

virtual reality modeling. from (burdea 1996) the vr physical modeling:

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