do these make any sense?

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Do these make any sense?. Navigation. Moving the viewpoint as a cost of knowledge. Navigation. Metaphors and methods Affordances Ultimately about getting information Geographic Space Non-metaphoric navigation. The affordance concept. Term coined by JJ Gibson (direct realist) - PowerPoint PPT Presentation

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Do these make any sense?

Navigation

Moving the viewpoint as a cost of knowledge

Navigation

Metaphors and methods Affordances Ultimately about getting information

Geographic Space Non-metaphoric navigation

The affordance concept

Term coined by JJ Gibson (direct realist) Properties of the world perceived in terms

of potential for action (physical model, direct perception)

Physical affordances Cognitive affordances

World-in-hand

Virtual scene

6 df HandleController

a

Flying Vehicle Control

Virtual scene

JoystickController

d

Walking interface

Virtual scene

TreadmillController

c

Walking-on-the-spot interface

Use in virtual reality system Actually a head bobbing interface.

Real-walking both more natural and better presence than either flying or walking on the spot.

Evaluation (Ware and Osborne 1990)

Exploration and Explanation Cognitive and Physical Affordance Task 1: Find areas of detail in the scene Task 2: Make the best movie

For examples see classic 3D user interaction techniques for immersive virtual reality revisited

World-in-handVirtual scene

6 df HandleController

a

Good for discrete objects

Poor affordances for looking scale changes – detail

Problem with center of rotation when extended scenes

Flying Vehicle ControlVirtual scene

JoystickController

dHardest to learn but most flexible

Non-linear velocity control

Spontaneous switch in mental modelThe predictor as solution

Eyeball in handVirtual scene

6 df HandleController

bEasiest under some circumstances

Poor physical affordances for many views

Subjects sometimes acted as if model were actually present

Map:ahead-upversustrack-up

NN

a b c

North-up for shared environment

Ahead-up for novices

View marker gives best of both

Mental maps

How do we encode space?

Seigel and White

Three kinds of spatial knowledge

1) Categorical (declarative) knowledge of landmarks.

2) Topological (procedural) knowledge of links between landmarks

3) Spatial (a cognitive spatial map).

Acquired in the above order

Colle and Reid’s study

Environment with rooms and objects Test on relative locations of objects Results show that relative direction was

encoded for objects seen simultaneously but not for objects in different rooms

Implications: can generate maps quickly: should provide overviews. (ZUIs are a good idea)

Lynch: the image of the cityLynch’s Types

Examples Function

Path Street, canal,

Transit line

Channel for movement

Edges Fence, Riverbank

District limits

Districts Neighborhood Reference

Region

Nodes Town square,

Public building

Focal point for

travel

Landmarks Statue Reference point

Vinson’s design guidelines

There should be enough landmarks so that a small number are visible.

Each Landmark should be visually distinct from others

Landmarks should be visible at all navigable scales

Landmarks should be placed on major paths and intersections of paths

Non-metaphoric Focus+Context

Problem, how not to get lost: Keep focus while remaining aware of the

context. Classic paper:

Furnas, G. W., Generalized fisheye views. Human Factors in Computing Systems CHI '86 Conference Proceedings, Boston, April 13-17, 1986, 16-23.

Non metaphoric Interfaces

ZUIs Bederson-Zooming Focus in context

Using 3D to give 2D context

Dill, Bartram, Intelligent zoom

Perspective wall

www.thebrain.com

Table Lenshttp://www.nass.usda.gov/research/Crop_acre97.html

POI Navigation MacKinlay

Point of interest. Select a point of interest Move the viewpoint to that point.

VP

+ View direction reorientation.

Dist =start

Ct

Center of Workspace Navigation

COW navigation Move objects to the center of the workspace.

Zoom about the center. Initially object-based became surface-based exponential scale changes d = kt

: a factor of 4 per second (10 sec ~ scale by a million) Better for rotations (people like to rotate around

points of interest)

COW Navigation in Graph Visualizer 3D Viewpoint

COW

The Concept: Translate to center of workspace then scale

GeoZui3DZooming + 2 dof rotationsTranslate point on surface to centerThen scale. Or translate and scale. (8 x per second)

Navigation as a Cost of Knowledge. How much information can we gain per unit time

Intra-saccade (0.04 sec) (Query execution) An eye movement (0.5 sec) < 10 deg : 1 sec> 20 deg. A hypertext click (1.5 sec but loss of context) A pan or scroll (3 sec but we don’t get far) Walking (30 sec. we don’t get far) Flying (faster , but can be tuned) Zooming, t = log (scale change) Fisheye (max 5x). DragMag (max 30x)

Generalized fisheye viewsGeorge Furnas

A distance function. (based on relevance) Given a target item (focus) Less relevant other items are dropped

from the display.

#include <GL/glut.h>

void redraw( void )

void motion(int x, int y) {

rx = x; ry = winHeight - y; }

void mousebutton(int button, int state, int x, int y) {

if (button == GLUT_LEFT_BUTTON && state == GLUT_DOWN)

{ rx = x; ry = winHeight - y;

} }

void keyboard(unsigned char key, int x, int y)

int main(int argc, char *argv[]){

glutMouseFunc( mousebutton);

glutMainLoop(); }

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