Klaas Werkman Arjen Vellinga Lecture 3: Interaction Klaas Werkman Arjen Vellinga

Contents Immersive Systems Non-immersive systems Input devices Virtual Model Body Model Non-immersive systems Input devices Tasks in Virtual Reality March 9th 2005 Lecture 3: Interaction

Interaction March 9th 2005 Lecture 3: Interaction

Types of tasks Navigation / Locomotion Object manipulation March 9th 2005 Lecture 3: Interaction

User properties that may influence the performance of a task User experience Domain knowledge Technical aptitudes Left-handed/right-handed Physical properties such as age, gender, size, stature March 9th 2005 Lecture 3: Interaction

Virtual Reality Model Participant should be immersed within the virtual world Participant should be able to directly manipulate the virtual world The environment should be intuitive to use The environment should have a natural set of interaction metaphors March 9th 2005 Lecture 3: Interaction

Immersion The displayed information surrounds the participant The display is extensive The display is inclusive The display is vivid March 9th 2005 Lecture 3: Interaction

Example immersive system Head Mounted Display (HDM) March 9th 2005 Lecture 3: Interaction

Another example March 9th 2005 Lecture 3: Interaction

Example semi-immersive system Cave Automatic Virtual Environment (CAVE) March 9th 2005 Lecture 3: Interaction

Difficulties interaction human and system Gulf of execution Gulf of evaluation March 9th 2005 Lecture 3: Interaction

Difference between CAVE and HMD with respect to interaction between human and system. HMD: Virtual body display Cave: Real body is visible March 9th 2005 Lecture 3: Interaction

Body Model Description of the interface to the Virtual Environment System Geometric description of the body drawn from an egocentric point of view March 9th 2005 Lecture 3: Interaction

H-Anim body hierarchy March 9th 2005 Lecture 3: Interaction

Motion tracking Animation March 9th 2005 Lecture 3: Interaction

Six properties of tracking systems Accuracy Resolution Range Total system lag Update rate Robustness March 9th 2005 Lecture 3: Interaction

Object manipulation example March 9th 2005 Lecture 3: Interaction

Locomotion March 9th 2005 Lecture 3: Interaction

Collision Detection Preventing object intersection Object pair collision detection; several tests to achieve this. March 9th 2005 Lecture 3: Interaction

Exhaustive test March 9th 2005 Lecture 3: Interaction

Basic rejection test 1 Each scene element is surrounded by a bounding sphere. Two objects cannot overlap if the distance between the two bounding sphere centers is greater then the sum of the radii of the bounding spheres. March 9th 2005 Lecture 3: Interaction

Basic rejection test 2 Separating plane test: Two objects cannot collide if any plane can be found where all the points of one object lie on one side and all the points of the other object lie on the other side. March 9th 2005 Lecture 3: Interaction

Basic rejection test 3 Bounding Box Range Test: Two boxes can overlap in 3D if and only if both their x-ranges overlap and both their y-ranges and both their z-ranges overlap. March 9th 2005 Lecture 3: Interaction

General Collision Detection With n objects n2 possible pairs of objects. Discard as many pairs as possible by spatial partitioning March 9th 2005 Lecture 3: Interaction

Spatial Division example March 9th 2005 Lecture 3: Interaction

Non-immersive Systems Desktop Virtual Reality Fish Tank Virtual Reality March 9th 2005 Lecture 3: Interaction

Characteristics of input devices Degrees of freedom Spatial resolution Sampling rate and system lag Resistance (isotonic or isometric) Body centered interaction Number of user supported Size, weight, comfort and mobility Costs March 9th 2005 Lecture 3: Interaction

6D Mouse March 9th 2005 Lecture 3: Interaction

Space ball March 9th 2005 Lecture 3: Interaction

Tablet March 9th 2005 Lecture 3: Interaction

Glove VPL Glove Cyberglove March 9th 2005 Lecture 3: Interaction

Taxonomy of Mackinlay The classification is: Linear / Rotary Position, Rotation / Force, Torque Relative / Absolute Direction Sensitivity (1 = discrete, 10 = small range, 100 = large range, INF = continuous) March 9th 2005 Lecture 3: Interaction

Taxonomy of Mackinlay March 9th 2005 Lecture 3: Interaction

Three types of composition Merge composition Layout composition Connection composition March 9th 2005 Lecture 3: Interaction

Magic Wand Animation March 9th 2005 Lecture 3: Interaction

Selection March 9th 2005 Lecture 3: Interaction

Object Manipulation Translation Rotation March 9th 2005 Lecture 3: Interaction

Translation March 9th 2005 Lecture 3: Interaction

Locomotion Metaphors Scene-in-hand — The scene itself is slaved to the input device Eyeball-in-hand — User viewpoint is controlled via direct manipulation of virtual camera Flying vehicle control — The input device provides the controls for the vehicle such as velocity and rotation Real world control — Walking, walking-in-place March 9th 2005 Lecture 3: Interaction

Locomotion March 9th 2005 Lecture 3: Interaction

Locomotion Scale Accuracy March 9th 2005 Lecture 3: Interaction