Input Devices and Interaction Techniques I. Scott MacKenzie Summarized and Augmented by Geb Thomas.

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Input Devices and Interaction Techniques I. Scott MacKenzie Summarized and Augmented by Geb Thomas

Transcript of Input Devices and Interaction Techniques I. Scott MacKenzie Summarized and Augmented by Geb Thomas.

Page 1: Input Devices and Interaction Techniques I. Scott MacKenzie Summarized and Augmented by Geb Thomas.

Input Devices and Interaction Techniques

I. Scott MacKenzie

Summarized and Augmented by Geb Thomas

Page 2: Input Devices and Interaction Techniques I. Scott MacKenzie Summarized and Augmented by Geb Thomas.

Introduction

• Input and output between people and machines

• New technology, new challenges

• Interaction experiments and models

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Transducers

• Convert energy -- often mechanical to electrical

• Switches (mechanical and photoelectric)• Isotonic (displacement) joysticks - position

encoders• Isometric (force sensing) joysticks - strain

guages• Microphones

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A Mouse

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Joysticks

http://www.vrealities.com/control.html

http://www.thevrsource.com/

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GlovesCyberglove

http://www.virtex.com/products/hw_products

Pinch glove

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TrackersPolhemus (Fast Track)

Flock of Birds (Virtex)

Intersence (IS300)

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Device Models

• Buxton’s taxonomy -- articulation, number of dimensions, type of sensing (position, motion, pressure), motor skills (touch vrs mechanical)

• Foley tasks -- select, position, orient, path, quantify and text entry -- emphasizes mappings

• Very few engineering models

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Device Parameters

• Resolution

• Sampling Rate

• Lag

• Optimality and control gain

• Some of these are determined by hardware, some by software, some by transducer characteristics

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Resolution

• Nonlinearity, monotonicity, offest and gain

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Sampling Rate

• Often 10-100 Hz

• Too slow for gesture capture

• Nyquest frequency

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Lag

• Time difference between controller input and display

• 3D trackers range 30 - 250 mx, depends on sampling rate, update rate and software overhead.

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Optimality and Control Gain

• Tunable parameters, such as mouse gain

• Selection task optimization does not consider “human engineering factors” such as – Ease of learning– skill retention– fatigue– effort– strees

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Mouse Gain

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Nonlinear Gain

Vd = k*Vc^2

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Interaction

• Movement is of increasing importance

• Many researchers considering mapping of 2D -> 3D

• Must be trained

• Limited metaphors

• Perceptual structure requires good match between input space and output space– Twisting for dials, shoving for movement, 2D for 2D,

3D for 3D

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Gestures

• The great new era :)

• Writing, scribbling, annotating, pointing, nodding, etc.

• Editing proofreaders marks

• Transcribing musical notation

• Brush strokes

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Tactile and Force Feedback

• Good input requires good feedback

• shape encoding in manual controls

• Character drawing the Octagon, a 24x6 matrix of pins

• Minski’s sandpaper

• Akamatsu and Sato’s variable friction

• Zimmerman’s pinch glove