Travel and Wayfinding
Techniques
Source & credits:
Prof.S.Feiner, Columbia U., N.Y.
Dr. L.Deligiannidis, U. of Georgia, GA
J.Sochor & students of HCILab, MU, CZ
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What is travel?
• the motor component of navigation
• movement between 2 locations, setting the
position (and orientation) of the user’s viewpoint
• the most basic and common VE interaction
technique, used in almost any large-scale VE
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What is travel?
Travel refers to the actual movement through
space, and not the planning, decision-making, or
cognitive aspects (wayfinding).
Can we really separate these 2 tasks?
You can have travel techniques which do not
address wayfinding, but the best travel techniques
will integrate travel techniques with aids to
wayfinding.
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What is travel?
We normally only consider setting the viewpoint
position when designing travel techniques for
immersive VEs, since orientation will be taken
care of with head tracking.
In non-immersive situations, travel techniques
must consider orientation, making them more
complex (e.g. navigation in a VRML browser).
Travel is truly a universal interaction task, except in
VEs in which all user interaction is local.
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Start to Move
Indicate position
– Specify Position
• discrete target specification (select object in environment,
from list, position 3D cursor, automatic selection, …)
• one-time route specification (markers, curvature, distance,
…)
• continuous specification (gaze directed, pointing, physical
steering, virtual controls, 2D pointing
– Specify Velocity
– Specify Acceleration
Indicate orientation
Stop moving
Travelling - Level of user control
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Travel subtasks
Direction/Target selection
– gaze-directed steering
– pointing/gesture steering
– discrete selection (lists,
environmental/direct targets)
– 2D pointing
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Travel subtasks
Velocity/Acceleration Selection
– Constant velocity/acceleration
– Gesture-based
– Explicit selection (discrete, continuous)
– User/environment scaling
– Automatic/adaptive
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Travel subtasks
Input Conditions
– Constant travel/no input
– Continuous input
– Start and stop inputs
– Automatic start or stop
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Travel tasks with respect to navigation
Exploration
– travel which has no specific target
– build knowledge of environment
Search
– naïve: travel to find a target whose position is not known
– primed: travel to a target whose position is known
– build layout knowledge; move to task location
Maneuvering
– travel to position viewpoint for task
– short, precise movements
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Travel - Exploration
Exploration tasks have no explicit goal of the
movement.
The user is simply exploring or browsing the 3D
space, usually to build knowledge of the
environment or to see what the interesting
features might be.
Travel techniques for exploration should be almost
thoughtless
– you want the user to be able to simply move about with
little restriction.
Video: zanbaka1
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Travel - Search
Search tasks involve traveling to a specific target
location in the environment.
Psychologists have further subdivided this task into
naive search, in which the position of the target is
not known, and primed search, in which the
position of the target is known (to some degree)
and the task is to find that location again.
See Darken & Sibert, CHI ’96, for use of these
tasks in a VE.
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Travel - Maneuvering
Maneuvering tasks usually involve short, precise
movements where the goal is to change the
viewpoint slightly in order to do a particular task.
In a surgery simulation, the doctor might need to
move to the other side of the operating table to get
a good view of the procedure he is performing.
In some cases, maneuvering can be allowed simply
by letting the user move physically.
However, due to limited tracker range, cable
tangling problems, etc. you sometimes have to use
an explicit travel technique for maneuvering.
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“Natural” travel metaphors
Walking techniques
– Large-scale tracking
– Walking in place (GAITER) - video
– CircularFloor - video
Treadmills
– Single-direction with steering
– Omni-directional
Bicycles
Other physical motion techniques
– VMC / Magic carpet
– Disney’s river raft ride
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“Natural” travel metaphors
Many people have worked on naturalistic travel
techniques that use physical motion and some
(pseudo) real-world metaphor for travel.
Obviously such techniques are useful for
applications such as training, where you want the
user to move about as she would in the physical
world to make the VE as lifelike as possible.
However, naturalism is not always the best choice.
We present here a few of the natural travel
metaphors, but will focus for the remainder of this
section on “virtual” or “magic” travel techniques
where little or no physical motion is involved.
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“Natural” travel metaphors
Naturalism also brings up the issue of realism in
general.
Too often it is asserted that VEs need to be realistic,
without defining what type of realism one means.
There is visual realism vs. realism of interaction,
for example.
Within interactive realism, it might be the case that
ITs for certain tasks need to be realistic, while others
do not.
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“Natural” travel metaphors
Walking techniques: these try to emulate
physical walking to allow full use of the vestibular
and kinesthetic senses.
A brute-force way to allow this is simply to expand the area
being tracked.
There are also efforts to in some way analyze the
user’s motions as he’s walking in place to
determine direction, speed, etc. The GAITER
project is one example.
Also, Iwata’s work has looked at different ways to
allow a more natural walking motion while not
physically translating, such as roller skates or slick
shoes on a slick floor.
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“Natural” travel metaphors
Treadmills: also designed to allow physical
walking or running, but using a bigger, more
expensive device.
Brooks at UNC used a standard exercise treadmill
outfitted with some steering apparatus for
movement in a VE.
The Torus treadmill (Iwata, IEEE Virtual Reality,
1999) is the omni-directional treadmill, which
allows walking in any direction. video
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“Natural” travel metaphors
Bicycles: have been used to simulate real motion
based on pedaling and force feedback.
In order to be realistic, you need to feel as if you’re
on a real bicycle, and simulate turning properly.
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“Natural” travel metaphors
Virtual Motion Controller
(VMC) – shown in the picture.
The VMC has sensors built into it
that sense the user’s weight and
thus which part of the platform he’s
centered over.
Direction of motion is controlled by
stepping in that direction on the
device.
Speed is controlled by distance from
the center.
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Virtual Motion Controller
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“Natural” travel metaphors
Magic carpet – this was a student project at
Georgia Tech very similar to the VMC.
Physically, it was a board on which the user stood.
9 regions were painted on the board allowing the
user to go in any of the 8 compass directions or
stop (by standing in the center).
River raft ride at Disney Quest – In this ride,
guests sit in a rubber raft on top of an inflatable
membrane which can simulate the water’s motion.
Motion is controlled by a combination of the
motions of all the guests’ paddles, allowing
steering, speed control, etc.
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Common virtual travel metaphors
steering: continuous specification of direction
of motion
– gaze-directed
– pointing
– physical device (steering wheel, flight stick)
target-based: discrete specification of goal
– point at object
– choose from list
– enter coordinates
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Common virtual travel metaphors
A very large number of different virtual travel
techniques (where there’s little or no physical
motion by the user) have been suggested and/or
implemented by researchers and application
developers.
Most of these techniques fall into four categories or
metaphors.
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Common virtual travel metaphors
The steering metaphor implies continuous control
of the direction of motion, as when you steer a car.
Examples
– gaze-directed steering: look in the direction you want to
go
– pointing: point in the direction you want to go
– using physical props such as a steering wheel, accelerator,
and brake
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Common virtual travel metaphors
The target-based metaphor lets the user choose
the end goal of the motion, then the system
actually performs the movement in between the
two points.
Examples
– point at the object to which you want to travel
– a menu or list of choices from which you make a selection
– enter the coordinates of the point to which you want to
move
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Target specification via object selection
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Map-based target specification
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Common virtual travel metaphors
route planning: one-time specification of path
– place markers in world
– move icon on map
manual manipulation of viewpoint
– “camera in hand”
– fixed object manipulation
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Planning a route with 2D map
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Common virtual travel metaphors
Route planning is a compromise between steering
and target-based metaphors: the user specifies the
end goal and also some intermediate path
information.
Examples
– using some manipulation technique, put markers in the
world to denote your path
– place markers on a map of the space
– move an icon representing yourself on a map of the space
(e.g. World-in-Miniature, Pausch, Burnette, Brockway, and
Weiblen, 1995)
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More common travel metaphors
Something different is manual viewpoint
manipulation, in which the user’s hand motions are
mapped in some way to viewpoint motion.
Examples
– camera in hand: the user moves his hand over a map of
the space, with his hand acting as the camera through
which the 3D space is viewed
– fixed object manipulation: the user selects an object
and moves his hand as if to manipulate the object’s
position. The object stays fixed and the user moves about
the object. The real-world analog of this is grabbing a
flagpole: when you move your hand, the flagpole stays put
and you move about it.
– grabbing the air: grab anywhere in the air or on the
world, and move the world relative to yourself rather than
moving yourself relative to the world. The realworld
analog of this is pulling yourself along a rope.
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Evaluation results
Steering techniques have similar performance on
absolute motion tasks
Non-head-coupled steering better for relative motion
“Teleportation” can lead to significant disorientation
Environment complexity affects the ability to gather
information while moving
Travel IT and user’s strategies affect spatial
orientation
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Evaluation results
Manipulation-based techniques not requiring an
object
- are efficient for search and relative motion, but
tiring
Map-based techniques not effective in unfamiliar
environments, or when any precision is required
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3 Myths on travel techniques
M1: There is one optimal travel technique for VEs.
M2: A “natural” technique will always exhibit more
performance, usability, and usefulness than
another technique.
M3: Desktop 3D, workbench, and CAVE applications
should use the same travel ITs as HMD-based VEs.
NO !
NO !
NO !
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Design guidelines
Make simple travel tasks simple (target-based
techniques for motion to an object, steering
techniques for search).
Provide multiple travel techniques to support
different travel tasks in the same application.
Use graceful transitional motions if overall
environment context is important.
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Design guidelines
Most travel tasks are simple in the mind of the user
– they just want to change their location while focusing on
something else.
Thus, you should use a technique that meets the
requirements of the task:
– e.g. use a target-based technique if the only goal is to
move between known objects
• don’t put unnecessary cognitive load on the user.
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Design guidelines
Remember the differences between tasks such as
exploration and primed search
– you may need more than one technique.
There is a tradeoff between the specificity of the
technique and the amount of learning load you
want to put on the user.
In many cases, multiple techniques requiring a bit
more learning time may be much more efficient in
the long run.
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Design guidelines
Many applications require the user to be aware of
their location within the space, have an overall
survey knowledge of the space, etc.
In these cases it is important to use transitional
motion between locations, even if it is fast, in
order to maintain awareness of the space.
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More design guidelines
Strategies (how the user uses the technique) are as
important as the technique itself, especially in tasks
requiring spatial knowledge. Therefore, you should
provide training, instructions, and guidance to help
the user take advantage of the technique.
Cross-task ITs can be useful if travel is not the
main interaction, but is only used, for example, to
gain a better viewpoint on a manipulation task.
Remember that such motion can be tiring,
however, and should not be used for very long
exposure period applications.
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Wayfinding
Wayfinding in virtual worlds used
to improve navigation in
• Real world
• Virtual world
Source: S Feiner, Columbia U., NY
Wayfinding is the cognitive process of defining
a path through an environment,
using and acquiring spatial knowledge,
helped by (artificial) cues
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Wayfinding
User makes decisions (whereabouts, trajectory) by
processing input (environmental information)
to produce output (travel)
Environmental information stored in LTM as
cognitive map
Wayfinding uses and builds cognitive map
Spatial orientation (knowledge of position and orientation)
Situation awareness (spatial orientation +
understanding of cognitive map + ability to predict)
Task-specific
“perception of elements in the environment within a volume
of time and space, the comprehension of their meaning and the
projection of their status in the near future” — M R Endsley, 1988
Source: S Feiner, Columbia U., NY
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Wayfinding
Model of navigation : Jul and Fumas (1977)
Source: R Darken & B Petersen 2002,
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
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Why is Wayfinding in 3D UIs Hard?
• Virtual worlds lack real world cues
Missing physical motion constraints
E.g., walls you can walk through
• Lack of motion (vection) cues
Use of virtual motion techniques or other
nonisomorphic motion techniques
• Constrained visual cues
Restricted FOV, detail, frame rate, …
Source: S Feiner, Columbia U., NY
6DOF makes wayfinding hard: human beings
have different abilities to orient themselves
in an environment,
extra freedom can disorient people easily
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Wayfinding
There are several particular differences between
real-world wayfinding and wayfinding in a virtual
world.
The added DoF´s make it harder for human beings
to find their way through a VE: whereas we are
normally used to being constrained in our actions
(i.e. gravity, walking on floors), we can often freely
fly through a VE.
The unconstrained behavior does not match with
how we move through a real environment.
This feeling is strengthened by the lack of of realmotion
cues we obtain during virtual movement.
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Wayfinding Tasks
Exploration
Browsing
Build cognitive map
Search
Acquire and use spatial knowledge
Naïve search
Target-based, but user doesn’t know exact target location
Primed search
Target-based with known target location
Relies on cognitive map
Maneuvering
Small scale movements to refine position/orientation
May be subtask of search
Specified trajectory movement
User travels along predefined path to build cognitive map
Source: S Feiner, Columbia U., NY
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Spatial Knowledge
Landmark knowledge
Important characteristics of environment
Perceptually prominent objects (landmarks)
Visual features: shape, size, color, texture
Procedural/route knowledge
Sequence of actions needed to follow a path
Survey knowledge
Topological knowledge of environment
Object locations/orientations, distances between objects
Map knowledge”
Requires longest time to achieve relative to others
Source: S Feiner, Columbia U., NY
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Approaches to Wayfinding
User-centered
Address human senses
Environment-centered
Address design of the environment
Source: S Feiner, Columbia U., NY
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User-Centered Wayfinding:
Field of View
Increasing FOV
Reduces need for head motion
Increases peripheral vision, including optical flow cues
Decreases cybersickness
Improves ability to understand spatial relationships
M Czerwinski, D Tan, and G Robertson, “Women take a wider
view,” Proc CHI 2002, 195–202.
Subjects navigate in 3D environment presented on
Small displays with a narrow field of view
Large displays with a wide field of view
Results
Narrow field of view: Men outperform women
Wide field of view: Women and men both perform better,
and gender bias is significantly reduced
Source: S Feiner, Columbia U., NY
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User-Centered Wayfinding
Motion (Vection) and Orientation Cues
• Visual cues
• Vestibular cues
Visual/vestibular conflict
• Tactile
• Proprioceptive
• Auditory
• Olfactory
Walking > Walking in place > Pure virtual
C Zanbaka et al., IEEE VR 2004 video
Source: S Feiner, Columbia U., NY
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User-Centered Wayfinding: Presence
Sense of “being there”
Measured by
Behavior: E.g., duck to avoid being hit, physiological
responses
Questionnaire responses
Aids effectiveness of real-world wayfinding
cues
Promoted by
Improved emulation of real-world effects
E.g., lack of lag, increased FOV
Virtual body
E.g., Looking down and seeing your feet
Source: S Feiner, Columbia U., NY
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User-Centered Wayfinding:
Search Strategies
Learn approach to aid effective wayfinding
(e.g., based on expert knowledge)
Search patterns/paths
Switching between egocentric and exocentric views
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Environment Design
Design environment for effective wayfinding
Legibility techniques
Real-world principles
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Environment Design: Legibility
Legibility
“the ease with which [a city’s] parts may be recognised and
can be organised into a coherent pattern”
— K Lynch, The Image of the City, 1960
Legibility Techniques (K Lynch)
Divide environment into distinct parts
Organize spatially to clarify relationships among parts
Use directional cues to support matching egocentric and
exocentric reference frames
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Environment Design: Legibility
Building blocks of cognitive maps
– Landmarks: Static, recognizable objects
– Districts: Sections of environment with distinct
character providing coherence
Style (architectural), color, lighting, use
– Paths: Major avenues of travel
Roads, footpaths
– Nodes: Points of interest on paths
Intersections, town squares
– Edges: Borders to districts or obstacles
Waterfront, “wrong side of the tracks”
May also serve as paths
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Environment Design: Real World Principles
• Natural environment
E.g., horizon, aerial perspective
• Built environment (architecture)
Illumination for recognizability/emphasis
Openings to guide users
• Use of color/texture to group and emphasize
in both natural and built environment
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues
• Maps
• Compasses
• Signage
• Reference objects
• Trails
• Grids
• Audio/olfactory cues
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
Graphic representation of
an area, drawn to scale
“You-are-here” map
Includes location marker
Orientation
North up: Better for exocentric
tasks
Forward up: Better for egocentric
tasks
Position/size
Fixed vs movable
User-controlled vs
system-controlled
Same display vs separate display
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/
Chapter28/Chapter28.html
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
Situation awareness aid controlled by head orientation:
yaw → yaw, pitch → pitch, position, scale, annotation
B Bell, T. Höllerer, and S Feiner, UIST 2002
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
Annotations move between real world and aid
B Bell, T. Höllerer, and S Feiner, UIST 2002
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
B Bell, T. Höllerer, and S Feiner, UIST 2002
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
B Bell, T. Höllerer, and S Feiner, UIST 2002
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
J LaViola, D Feliz, D Keefe, & R Zeleznik, SI3D 2001 ,
Step WIM
WIM on the floor
Invoked by toe tap
User walks around WIM
Toe tap
Dismisses WIM
if user looking up
Goes to current location
if user looking down
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Maps
J LaViola, D Feliz, D Keefe, & R Zeleznik, SI3D 2001
Step WIM
WIM scale mode invoked by
heel click
User walks relative to original
position at click to scale
WIM up/down
User clicks heels again
to exit scale mode
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Compasses
Pointer to north or
other designated
object
Typically always visible
E.g., Floating compass
arrow pointing north
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Compasses
Pointer to north or other
designated object
Typically always visible
E.g., Currently selected
object pointer rotating
in image plane
Columbia Mobile Augmented Reality System
www.cs.columbia.edu/graphics/projects/mars/marsUIs.html
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Signs
Displays identifying objects or places
E.g., labels
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Reference Objects
Objects of known scale
Facilitate measurement of size and distance
E.g., people
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Artificial Landmarks
Objects added specifically
for wayfinding
Distinguishable
Positioned for recognizability
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Trails
Objects added to
show user’s path
• E.g., lines,
breadcrumbs,
footprints (showing
direction)
• Could have
functionality for
following
• Cause clutter if left
indiscriminately
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
Source: S Feiner, Columbia U., NY
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Environment-Centered Wayfinding
Artificial Cues: Trails
Source: S Feiner, Columbia U., NY
Objects added to
show user’s path
• E.g., lines,
breadcrumbs,
footprints (showing
direction)
• Could have
functionality for
following
• Cause clutter if left
indiscriminately
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
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Environment-Centered Wayfinding
Artificial Cues: Grids
Regular ruled overlays
Partition environment
Allow users to determine
current partition,
organize search
E.g., radial, rectangular
R Darken & B Petersen 2002
vehand.engr.ucf.edu/handbook/Chapters/Chapter28/Chapter28.html
Source: S Feiner, Columbia U., NY
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Wayfinding Evaluation
• Time to target
• Path analysis
Length
Unnecessary turns
Repetition
• Ability to draw layout
sketches
Number of (in)correct objects
Relative/absolute object
Size
Orientation
Position
Paths in targeted map searches (with target on map):
(A) Forward-up, (B) North-up
R Darken & H Cevik, IEEE VR 99
Source: S Feiner, Columbia U., NY
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Design Guidelines
• Match the cue to the task (e.g., maps for physical
environments, but not necessarily for abstract
data sets)
• Match the cue to the user’s skills
• Don’t make cues dominant features
Source: T Höllerer, UCSB
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Design Guidelines
• Choose input devices providing real motion cues
if possible
• Use animation, avoid teleportation
• Integrate travel and wayfinding components
Source: T Höllerer, UCSB
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Design Guidelines: Maps and Landmarks
• Use YAH (You-Are-Here) maps
• Consider multiple maps at different scales
• Carefully choose orientation
• Ensure legibility
• Use appropriate size and placement
(reduce occlusion)
• Carefully place and distinguish landmarks
Source: T Höllerer, UCSB