Representing People in Virtual Environments Will Steptoe 17 th - - PowerPoint PPT Presentation

Representing People in Virtual Environments

Will Steptoe 17th November 2009

What’s in this lecture?

First Hour

Overview and Applications

• State-of-Art, Social Agency, Human Behaviour, Realism,

Applications, Agency (Agents and Avatars), CVEs, Avatar Control.

Second Hour Technical Aspects and Demonstration

• Graphics, Animation, Behaviour
• Application in 3DSMax

INTRODUCTION

State-of-Art

Real-Time Pre-Rendered

Heavy Rain Quantic Dream, 2009 The Curious Case of Benjamin Button David Fincher, 2008

INTRODUCTION

Virtual Humans

• Complex problem of technical and human factors.
• Generating subtleties of human behaviour is a

problem beyond raw computing power. The more real they look, the more real we expect them to behave.

• To generate completely realistic characters we

have to completely understand human perception in reality!

• ... but why are we so sensitive to minor defects in

virtual humans?

INTRODUCTION

Social Agency and the ELIZA effect

• People generally require minimal encouragement

to view computer systems and applications as social agents, reading far more understanding than is warranted from symbols and graphical displays.

“Individuals mindlessly apply social rules and expectations to computers” – Nass and Moon, 2000.

• This was unexpectedly observed, and first

documented, by Weizenbaum (1966) when performing user studies with ELIZA - a computer program for the study of natural language communication between man and machine.

SOCIAL AGENCY

Social Agency and the ELIZA effect

• During the purely text-based interactions between

participants and the system, ELIZA simulated a Rogerian psychotherapist by rephrasing input statements from the user, and returning them as

• questions. (i.e. “I’m feeling depressed” -> Why do

you think you are feeling depressed?)

• Weizenbaum observed many examples of people

becoming emotionally engaged when ‘communicating’ with ELIZA, and some even asked to be left alone with the system.

SOCIAL AGENCY

Social Agency and the ELIZA effect

• This phenomenon has become known as the

‘ELIZA effect’, and may be considered a precursor to many observations found in the VE literature concerning presence (place illusion) and copresence.

• People are particularly responsive to depictions
• f humans.

SOCIAL AGENCY

• David
• Not very comfortable

with public speaking

• Asked to speak about

his favourite subject: cables

• Behaviours triggered

at appropriate intervals

Pertaub, D.-P., Slater, M., and Barker, C. (2002). An experiment on public speaking anxiety in response to three different types of virtual audience. Presence: Teleoperators and Virtual Environments, 11(1): 68-78

The Fear of public speaking

SOCIAL AGENCY

The Fear of public speaking

• The user was asked to give a presentation three times

– Positive, Negative and Mixed

• Positive - agents smiled, leaned forward, faced the user,

maintained gaze, clapped hands, etc.

• Negative - agents yawned, slumped forward, put feet on

the table, avoided eye contact, and finally walked out

• Mixed - agents started off with largely negative

responses and gradually turned positive

SOCIAL AGENCY

Realistic responses in VE ?

• Individuals' self-rated performance was positively

correlated with the perceived good mood of the agents

• Evidence of a negative response especially strong

with the negatively inclined audience – Sweating and stammering – Vocal protests at the agent behaviours

• Virtual humans with minimal behavioural-visual

fidelity can elicit significant user responses

• End Goal: Virtual humans with high visual fidelity

that mimic real-life context-appropriate behaviours

SOCIAL AGENCY

Categories of behavioural cues

• Vocal properties

– Tone, Pitch, Loudness…

• Facial expressions

– The most studied behavioural cue due to it’s role in communication

• Gaze behaviour

– Probably the most intense social signallers

• Kinesics: Posture and Motion

– Numerous gestures depending on culture for instance

• Proxemics

– Culture and gender dependent

Argyle, M. (1998). Bodily Communication. Methuen & Co Ltd, second edition.

HUMAN BEHAVIOUR

Facial expression

• In reality, 20000 facial expressions exist
• Normally animated by blending “Morph Targets”
• Different granularities of facial expression

– Facial action parameters (most basic units)

• Basic emotions

– Phonemes (mouth shapes for lip-sync) – Principal component analysis HUMAN BEHAVIOUR

Gesture

• Normally animated by choosing from a library of

gestures

• Very closely associated with speech

– Also back channel gestures by listeners (e.g. head nod)

• Different types of gesture

– E.g. beat, iconic

• Again see Cassell’s work referenced earlier

HUMAN BEHAVIOUR

Posture

• Over 1000 stable postures

have been observed

• Normally animated by

choosing from (or blending between) a library of gestures

• Associated with attitude

and emotion

• Associated also with

interpersonal attitude

Coulson, M. (2004). Attributing emotion to static body postures: Recognition accuracy, confusions, and viewpoint dependence. Journal of Nonverbal Behavior, 28(2):117–139.

HUMAN BEHAVIOUR

Measuring Success

• So the careful design of behaviour is important but there

are caveats

• Success of a VE is measured in terms of the extent to

which sensory data projected within a virtual environment replaces the sensory data from the physical world

– quantified by rating the individuals’ sense of presence during the experience

• For Virtual Humans: Success is taken as the extent to

which participants act and respond to the agents as if they were real

– Subjective: Questionnaires, Interviews – Objective: Physiological, Behavioural

HUMAN BEHAVIOUR

Subjective means

• Traditional methods: Questionnaires and

interviews

– Various questionnaires exist – http://www.presence-research.org

• Criticised due to its various dependencies

– the individual’s accurate post-hoc recall, – processing and rationalisations of their experience in the VE and – Varying interpretations of the word ‘presence’ HUMAN BEHAVIOUR

Objective: Responses to stimuli

• Numerous possible objective measures

– Subconscious responses

• Threat-related facial cues provokes individuals to use different viewing

strategies

– Neural responses

• Different areas of the brain are activated during +ve, -ve and neutral

situations

– Psychological responses

• Stress and Anxiety in response to threat

– Physiological responses

• Galvanic Skin Responses, Heart Rate Variability, electrocardiograms,

electromyography, Respiratory activity

– Behavioural responses

• Flight or Fight (based on cognitive appraisal)
• Vary based on cognitive factors, personality,

emotional state, gender etc.

– How do we interpret the data and results? HUMAN BEHAVIOUR

Uncanny Valley

• As the behaviour and representation of robots

(and other facsimiles) of humans approaches that

• f actual humans, it causes a response of

revulsion among human observers.

• Theory from 70s by roboticist Masahiro Mori

– Controversial, its not very rigorous or scientific, many people don’t believe it – There are problems but maybe it captures something REALISM

The Uncanny Valley

REALISM

The Uncanny Valley

Dreamworks reduced realism of Princes Fiona (Shrek):

“…she was beginning to look too real, and the effect was getting distinctly unpleasant.”

Final Fantasy movie:

“…it begins to get grotesque. You start to feel like you're puppeteering a corpse”

REALISM

REALISM

Uncanny Valley

• At low levels of realism, the more realistic a

character the more people like it.

• But when you get almost real then characters start

to get disturbing - corpses are used a lot as metaphors

• Interestingly, there are two graphs: movement and

appearance, movement is more important.

REALISM

Different Types of Realism

• Visual Realism

– What it looks like (pictures, film, games, VE)

• Animation Realism

– How it moves, animation (film, games, VE)

• Behavioural Realism

– How it responds and interacts (games, VE) REALISM

Mismatch in Realism

• Maybe the problem is that levels of movement

and behavioural realism do not match graphical realism.

• This mismatch disturbs us, something that

looks human but does not act like a human.

• Consistency is important.

REALISM

Appearance vs. Behaviour

Vinayagamoorthy, V., Garau, M., Steed, A., and Slater, M. (2004b). An eye gaze model for dyadic interaction in an immersive virtual environment: Practice and

• experience. Computer Graphics Forum, 23(1):1–11.

REALISM

Appearance vs. Behaviour

App. Beh. Cartoon – Form Higher – Fidelity Random gaze 3 ♂ pairs 3 ♀ pairs 3 ♂ pairs 3 ♀ pairs Inferred* gaze 3 ♂ pairs 3 ♀ pairs 3 ♂ pairs 3 ♀ pairs App. Beh. Cartoon – Form Higher – Fidelity Random gaze High Low Inferred* gaze Low High

Garau, M., Slater, M., Vinayagamoorthy, V., Brogni, A., Steed, A., and Sasse, A. M. (2003). The impact of avatar realism and eye gaze control on the perceived quality of communication in a shared immersive virtual

• environment. In Proceedings of SIGCHI, pages 529–536.

REALISM

Appearance vs. Behaviour

• Realistic gaze behaviour had a positive impact on the

perception of more visually-realistic avatars.

• In the case of a lower visually realistic avatar, the more

complex gaze model had a negative effect on participant response.

• Important to note that the differences between both the

gaze models were very subtle – saccadic velocity and fixation durations.

• Analysis demonstrated a very strong interaction effect

between the type of avatar and the fidelity of the gaze model.

REALISM

Realism vs Believability

• The lesson is that we need to be careful with

realism for virtual humans

• Often we prefer to use the term “believability”

– Not how much a character is objectively like a human – How much we feel it is/respond to it as if it is – Bugs Bunny is very believable

• Photorealism is only one element of believability

– But don’t turn into an anti-realism zealot! REALISM

Characters in Virtual Environments

• So far we have talked about how people respond

to characters.

• Now we will talk about characters in virtual

environments

• Characters are often key to an environment, the

primary content

• We are interested in people so populated

environments are interesting

APPLICATIONS OF VIRTUAL CHARACTERS

Applications of Virtual Characters

Games

Non-player characters are generally there to either be shot, or to have more complex interactions with. Player-characters are represent the user.

Online Virtual Worlds

Users are represented by avatars – an iconic representation of a human. Interaction via text, voice and nonverbal (scripted animation) means.

Immersive VEs

Users are embodied by avatars – natural body movement is mapped to avatar animation.

APPLICATIONS OF VIRTUAL CHARACTERS

Multi-user worlds

• Avatars become much more important in multi-

user worlds (the most important feature?)

• They also represent you to other people
• They affect how people perceive you

APPLICATIONS OF VIRTUAL CHARACTERS

Multi-user worlds

• Established norms of proxemic and gaze

behaviour are preserved in VEs: male-male dyads maintain greater interpersonal distance than female-female dyads, male-male dyads maintain less eye contact than female-female dyads, and decreases in interpersonal distance are compensated with gaze avoidance (Yee 2007).

• Echoes Argyle et al.’s equilibrium theory

specifying an inverse relationship between mutual gaze and interpersonal distance

APPLICATIONS OF VIRTUAL CHARACTERS

Immersive VR

• In immersive VR systems you can interact with life

size, real-time characters that may be agents (autonomous), avatars (other human users) or hybrids.

APPLICATIONS OF VIRTUAL CHARACTERS

Agency: Avatars and Agents

• Characters in virtual environments fulfill many

roles but there are two primary types

• Avatars

– Representations of you, or other people – User controlled (tracked)

• Agents

– Others, that you interact with – Computer Controlled

• Hybrid

– Part tracked, part simulated AGENCY

Agency: Avatars and Agents

• In practice some elements
• f avatar behaviour are

programmed not tracked

• E.g., breathing and eye

blinking at the least

• Ideally can use information

about ‘mood’ to determine aspects of avatar behaviour.

• Impossible to track every

aspect of the human’s behaviour so much must be inferred and programmed.

• Real avatars are mixed.

Avatar Agent Tracking Programming Mixture of both

AGENCY

Agency: Avatars and Agents

• For agents the behaviour is completely

programmed.

• For avatars the behaviour is ideally completely

determined by the behaviour of the real tracked human.

• In practice the human cannot be fully tracked –

typically in VR only head and one hand movements are tracked!

AGENCY

Interactive Behaviour

• Key to both roles is the interaction with a

character

• Composed of two elements, UI and AI
• “User interface”

– In what ways do we interact with a character?

• “Artificial (Augmented) Intelligence”

– How does the character respond? – How is it controlled? AGENCY

Agents

• Many different style of interaction for agents
• Cannon fodder, non-player characters, crowds,

complex conversational agents

• Many interactions, shooting, moving, conversation

(from dialogue trees to spoken interaction)

AGENTS

Agents - Game NPC

• UI:

– Moving, shooting – Simple conversation

• AI:

– Finite state machines – Scripts – Path Planning AGENTS

Virtual Humans - Agents

http://www.miralab.unige.ch Agents are entirely program controlled rather than representing an on-line human. These are examples from virtual fashion shows.

AGENTS

Agents - Embodied Conversational Agents

• UI:

– Speech conversation – Gestures etc. – Tracking data

• AI:

– Complex conversational – AI methods AGENTS

Inferring Behaviour: Animation imitating life

• Emotional models

– Controllers of behaviour in accordance to internal states

• Personality models

– Creating unique identities

• Conversation-feedback models

– Controlling behaviour

• Social models

– Interpersonal relationships and attitudes

• ???

Lasseter, J. (1987). Principles of traditional animation applied to 3d computer animation. ACM SIGGRAPH Computer Graphics, 21(4):35–44.

AGENCY

Avatars

• Your embodiment in the VE
• A vital part of shared VEs
• Generic or personalised
• User embodiment in shared VEs is the

fundamental mediator of the visual interaction, functioning both to identify users and to communicate nonverbal behaviour including position, identification, focus of attention, and gesture and actions (Thalmann 1999)].

AVATARS

Avatars

• Avatars generally exhibit generic humanoid

form, reflecting their status as a representation of a human user, and critically, enables direct relationship between the user’s natural bodily movement, and the corresponding animation of their avatar embodiment in the VE.

• Relates back to social agency and presence.

AVATARS

Avatars

• Useful and interesting applications are

with other people

– Simulation of real events – Training – Entertainment – Shared VEs

• The other users are entirely ‘real’ but

represented entirely synthetically

– As in shared (networked VEs)

AVATARS

Collaborative Virtual Environments (CVEs)

• Can be immersive (i.e. CAVE) or non-immersive

(i.e. desktop)

• Avatars are the visual mediator of communication
• Differing control metaphors:

– In immersive system, avatars embody the real tracked person in terms of spatial representation (where they are, what they are looking at) and behavioural representation (what they are doing). – In non-immersive systems, avatar control is performed by standard input devices as no tracking is available. AVATARS IN CVEs

Avatars and Identity

• Users of online virtual worlds use avatars as a

means of identity creation

• Customization is vital

– Appearance, clothes, hair, sometimes animation

• The relationship to real identity is complex

– Have a different appearance, personality, gender – Explore hidden sides of yourself – Some people feel their avatar is “More Me” than their physical self AVATARS IN CVEs

Avatars as social tools

• Ideally avatars is social VEs should support social

interaction

• Display the bodily functions of communication

(body language)

• However, most avatars in most virtual worlds don’t
• The body movements often exist, but most users

use them unrealistically or often not at all

• Primarily a problem of control

AVATARS IN CVEs

Avatars in Immersive CVEs

Allows spatial interaction more easily than other telecommunication systems such as video. Spatiality is a natural feature of the real-world.

AVATARS IN IMMERSIVE CVEs

Avatar Mediated Communication

AVATARS IN IMMERSIVE CVEs

Hardware and software work together to approximate reality:

• Life-size representations
• Body tracking coupled to avatar movement - head and

hand at least as these are the prerequisite tracking devices used in immersive systems.

• Stereo visualisation

Avatar Mediated Communication

AVATARS IN IMMERSIVE CVEs CVE hardware and software are usually decoupled. This means that the same software will operate

• n many hardware systems.

Asymmetric collaboration is possible (i.e. a user in the CAVE and a user on a mobile device). Each user views and interacts via input devices appropriate to their hardware.

Controlling avatars

• Typed Text, Emoticons, Traditional GUI, Speech,

Full body tracking

AVATAR CONTROL

Minimal Tracking for IK in VR

• Badler et al showed a minimal

configuration for IK representing the movements of a human in VR

– www.cis.upenn.edu/ ~hollick/presence/presence.html

• It was shown that 4 sensors are

sufficient to reasonably reconstruct the approximate body configuration in real-time. AVATAR CONTROL

Nonverbal Expression – tracking vs simulation

Key limiting factor of avatar-mediated communication is the lack of nonverbal communication (NVC). Avatars are primitive when compared to video of real people. In AMC, NVC behaviours can modelled (thus forming a hybrid avatar-agent), but models are unable to communicate the subtleties of human behaviour and the unpredictability of social interaction. Also, models are not faithful to the controlling user’s behaviour, so may communicate incorrect signals.

AVATAR CONTROL

Nonverbal Expression – tracking vs simulation

Tracking is the solution, but is difficult. Implement tracking behaviour according to priority:

• 1. Body motion
• 2. Eye movements
• 3. Facial expression
• 4. ...... ?

AVATAR CONTROL

Problems with Controlling Avatars

• Two modes of control: at any moment the user must

choose between either selecting a gesture from a menu or typing in a piece of text for the character to say. This means the subtle connections and synchronisations between speech and gestures are lost.

• Explicit control of behaviour: the user must consciously

choose which gesture to perform at a given moment. As much of our expressive behaviour is subconscious the user will simply not know what the appropriate behaviour to perform at a give time is [BodyChat, Vilhjalmsson, H. and Cassell, J., 1998] AVATAR CONTROL

Problems with Controlling Avatars

• Emotional displays: current systems mostly concentrate on

displays of emotion whereas Thórisson and Cassell (1998) have shown that envelope displays – subtle gestures and actions that regulate the flow of a dialog and establish mutual focus and attention – are more important in conversation.

• In non-immersive CVEs only: direct tracking of a user’s

face or body does not help as the user resides in a different space from that of the avatar and so features such as direction of gaze will not map over appropriately. [BodyChat, Vilhjalmsson, H. and Cassell, J., 1998] AVATAR CONTROL

Solutions

• Always ensure that any control is done through a

single interface (e.g. through text chat)

• BUT….
• The body language of an avatar should be largely

autonomous, and indirectly controlled by users

• Minimize the level of control needed

[BodyChat, Vilhjalmsson, H. and Cassell, J., 1998] AVATAR CONTROL

Solutions: Spark

• Text Chat based

environment

• Parse users text

input for interactional information

• Use this information

to generate behaviour

AVATAR CONTROL

Solutions: Spark

AVATAR CONTROL

Solutions: PIAVCA

User Interaction Script Database Motion Queue Operator Speech Generation Final Animation Gaze Posture Shifts Proxemics Concurrent Behaviours

Speech Movements Multi-model utterances

AVATAR CONTROL

Designing virtual humans

• GOAL: Represent the Person in VE consistently

– With perceived realism, believability …

• Induce responses to the virtual human

– Inducing realistic/lifelike responses

• Enhancing collaborative experience
• Facilitate social communication and interpersonal

relationships

GOAL OF VIRTUAL HUMANS

Designing behaviour

• Creating apparent social intelligence is

challenging

• Have to present behavioural cues to depict a

perceived (and plausible) psychological state

– Or the near-truth internal state of the Person being represented

• Human behaviour is a very intricate phenomenon

– Dependent on many factors

• Extremely difficult to replicate especially if the

design process is approached in an ad-hoc manner

– For instance: In social interactions within VE, the more visually realistic the virtual human, the more naturalistic users expect it to act

GOAL OF VIRTUAL HUMANS

Summary

• Social agency ensures that virtual human agents are able

and necessary to represent social situations

• Gamut of human behaviour ensures that this is a very

complex problem which should be adapted to application.

• Higher realism (behavioural and visual) is not necessarily

a good thing.

• Avatars and Agents must capture social intelligence using

tracking or simulation of behaviour. The design of these should consider to many factors, again including application.

• Avatars typically need to be a mixture based on tracking

data and inferred state.

• Current Research focus on quantifying the successful

creation of Virtual Humans using objective measures. GOAL OF VIRTUAL HUMANS

End of Part 1 3DSMax Demo

Technical Aspects of Virtual Characters

• Graphics

– Polygon meshes, rendering

• Animation

– Skeletal animation, mesh morphing, physical simulation

• Behaviour

INTRODUCTION

Graphics

• Techniques: Meshes, texture mapping, standard

graphics stuff

• Hand modelling: can be cartoony or highly realistic
• 3D Scanning/phototextures: can have very high

realism

• Rendering Opacity: Subsurface scattering

INTRODUCTION

Modelling

Scanned body results in huge mesh which can be rendered at different resolutions (numbers of polygons)

INTRODUCTION

Animation – bones and morphs

INTRODUCTION

Body Animation

• Can Hand animate the

skeleton

• Often use motion capture
• Real data = Realism (?)

MOTION CAPTURE

Marker-based Capture

• Able to capture subtle facial expressions of actors
• Not real-time (require intensive post-processing)
• Less reusable (i.e. Skeletal motion capture can be

applied to any model, but facial motion capture is more specific to a particular model).

MOTION CAPTURE

Skeletal Animation

• The fundamental aspect of human body motion is

the motion of the skeleton

• The motion of rigid bones linked by rotational

joints (first approximation)

• I will discuss other elements of body motion such

as muscle and fat briefly later

SKELETAL ANIMATION

Typical Skeleton

• Circles are rotational joints

lines are rigid links (bones)

• The red circle is the root

(position and rotation offset from the origin)

• The character is animated

by rotating joints and moving and rotating the root SKELETAL ANIMATION

Forward Kinematics (FK)

• The position of a link is calculated by

concatenating rotations and offsets

O0 R0 O1 O2 R1 P2 SKELETAL ANIMATION

Forward Kinematics (FK)

• First you choose a position on a link (the end point)
• This position is rotated by the rotation of the joint

above the link

• Translate by the length (offset) of the parent link and

then rotate by its joint. Go up it its parent and iterate until you get to the root

• Rotate and translate by the root position

SKELETAL ANIMATION

Forward Kinematics (FK)

• Simple and efficient
• Come for free in a scene graph architecture
• Difficult to animate with,

– often we want to specify the positions of a characters hands not the rotations of its joints

• The Inverse Kinematics problem:

– Calculating the required rotations of joints needed to put a hand (or other body part) in a given position. SKELETAL ANIMATION

Inverse Kinematics

• An number of ways of doing it
• Matrix methods (hard)
• Cyclic Coordinate Descent (CCD)

– A geometric method (secretly matrices underneath) R1 Pt R0 O1 O2 SKELETAL ANIMATION

Inverse Kinematics

• Start with the final link

SKELETAL ANIMATION

Inverse Kinematics

• Rotate it towards the target

SKELETAL ANIMATION

Inverse Kinematics

• Then go to the next link up

SKELETAL ANIMATION

Inverse Kinematics

• Rotate it so that the end effector points towards the target

SKELETAL ANIMATION

Inverse Kinematics

• And the next…

SKELETAL ANIMATION

Inverse Kinematics

• And the next…

SKELETAL ANIMATION

Inverse Kinematics

• And iterate until you reach the target

SKELETAL ANIMATION

Inverse Kinematics

• And iterate until you reach the target

SKELETAL ANIMATION

Inverse Kinematics

• And iterate until you reach the target

SKELETAL ANIMATION

Inverse Kinematics

• And iterate until you reach the target

SKELETAL ANIMATION

Inverse Kinematics

• And iterate until you reach the target

SKELETAL ANIMATION

Inverse Kinematics

• IK is a very powerful tool
• However, it’s computationally intensive
• IK is generally used in animation tools and for

applying specific constraints

• FK is used for the majority of real time animation

systems

SKELETAL ANIMATION

Representation and Format

• Layered representation

– Skeleton structure forms a scene graph – Scene graph embodies a set of joints – A mesh overlays the scene graph – As the skeletal structure moves the mesh must deform appropriately (otherwise there are holes)

MPEG4 example

http://ligwww.epfl.ch/~maurel/Thesis98.html

SKELETAL ANIMATION

Facial Animation

• Don’t have a common

underlying structure like a skeleton

• Faces are generally

animated as meshes of vertices

• Animate by moving

individual vertices MORPH TARGET ANIMATION

Morph Targets

• Have a number of facial expressions, each

represented by a separate mesh

• Each of these meshes must have the same

number of vertices as the original mesh but with different positions

• Build new facial expressions out of these base

expressions (called Morph Targets)

MORPH TARGET ANIMATION

Morph Targets

MORPH TARGET ANIMATION

Morph Targets

• Smoothly blend between targets
• Give each target a weight between 0 and 1
• Do a weighted sum of the vertices in all the

targets to get the output mesh

∑ ∑

= =

∈

1 ;

ets morph_targ t t ti t i

w v w v

MORPH TARGET ANIMATION

Using Morph Targets

• Morph targets are a good low level animation

technique

• Also need ways of choosing morph targets
• Could let the animator choose (nothing wrong with

that)

• But there are also more principled ways.

MORPH TARGET ANIMATION

Summary

• Characters are represented typically as

‘skinned’ skeletal scene graphs, representing sets of joints that link to the geometry.

• Forward kinematics determines overall

configuration given joint angles and Inverse kinematics determines joint angles from requirements for end-effectors

• Morph targets are a method of mesh

deformation often used for facial animation

END!