This slideshow for HUMAN COMPUTER INTERACTION subject

1. HUMAN COMPUTER
INTERACTION
SUBJECT CODE : DCM 214
Prepared by : NURAINI MOHD GHANI
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Chapter 2
HUMAN CAPABILITIES :
INPUT OUTPUT SYSTEMS

2. KEY POINT
Human have processing constraints
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Motor limitations, e.g. Fitts’ law for pointing
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Visual range for motion, shape, colour, detail and
their consequences for design decisions
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Visual attention models
Alternative sensory channels
Alt ti h l
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3. HUMAN CONSTRAINTS
What do we know about human capabilities that could or
should constrain interface design?
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Limits on perceptual capability – e.g. contrast, resolution
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Limits on motor capability – e.g. reach, speed, precision
Limits on attention capacity
Limits on memory
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Rates of learning and forgetting
Causes of error
Mental
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Individual differences (the average size fits few people)
Variable state (e.g. stress, fatigue)
Special needs & age … 3

4. HUMAN CONSTRAINTS
Model Human Processor
(MHP)
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*One way to subdivide
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the main constraints
*Perceptual, Motor and
Cognitive sub-systems
sub systems
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characterised by:
– Storage capacity U
– Decay time D
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– Processor cycle time T
*We will focus today on
the perceptual and 4
motor processes

5. MOTOR CONSTRAINTS
Example: Fi ’ law (1954)
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6. MOTOR CONSTRAINTS
Example: Fitts’ law (1954)
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Justification?
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#By “analogy” to Shannon information
capacity = bandwidthxlog2((signal+noise)/noise)
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#If move fraction 1-r to target each timestep,
then reach target when rnD = W/2; so n is
proportional to log22D/W
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# Empirically find good fit with log2(D/W + 0.5)

7. MOTOR CONSTRAINTS
Example: Fitts’ law (1954)
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Application?
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*Time will increase with distance – can we
keep everything close?
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*Time will decrease with width – can we
make width infinite?
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8. Prepared by : NURAINI MOHD GHANI
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PERCEPTION
What can we see?

9. PERCEPTION
Some consequences of what we can see:
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#Motion – will be visible (and distracting)
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anywhere in visual field
# Colour – main advantage is “pop-out”:
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But many disadvantages:
# Sh
Shape iimportant i t t recognition: SO
t t in text iti
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ALL CAPS BAD
# Limits on resolution – recommend
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minimum font size; ideally individual can adjust
# High resolution only in tiny area of fixation
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10. EYE TRACKING
Fixation pattern is a g
p good indicator of attention
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#Where do people look, how often, for how
long, in what order?
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#Recent technology is making this a
standard tool for HCI
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#Also used as input device.
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11. PERCEPTION
Importance of eye movements
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Must shift the tiny high
resolution area around
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Constantly
Movements called saccades
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occur > 2 per second all day Long
How does visual system decide
where to move next?
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Models of attention
e.g. Itti et.al. 1998
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12. ATTENTION
Simple statistical model of saliency Rosenholtz et al (2005)
*Provides definition of ‘clutter’: size of
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local covariance ellipsoid
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* To measure:
* Compute local feature covariance at
multiple scales
* Take maximum across scales
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* Average for different features
* Pool over space
*P d
Produces good correlation with human
d l ti ith h
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estimates of clutter
* Can also use to determine what
feature added where would best draw 12
attention

13. ATTENTION
#So what went wrong here?
#Task: find current population of U.S.
k fi d l i f S
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86% of users failed…
http://www.useit.com/alertbox/fancy-formatting.html 13

14. PERCEPTUAL CONSTRAINTS
Bottom up visual processing sets some constraints on
optimal layouts, but must also consider top down
ti l l t b t t l id t d
issues:
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#Cultural and l
#C lt l d learned f t
d factors – f ili it
familiarity
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#Underlying domain knowledge of user
# Need to reflect logical structure, e.g., placement and
grouping
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according to function, sequence, frequency of use
# Dependence on task to be carried out, e.g. getting an
overview
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vs. seeking specific information
# Note that layout and visualisation are already widely
explored fields with conclusions that carry over to
fields, 14
HCI

15. ALTERNATIVE SENSORY CHANNELS
Different sensors provide parallel channel capacity
Sound:
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#Not so easy to localise but can detect from any direction
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# Grabs attention – warning mechanisms
# Good signal of causal relation – use as confirmatory
feedback
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# Monitoring state, ‘background information’
# Disk, printer noise etc.
# Example of user improvisation in use of ‘data’
data
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# Interface sound design is typically arbitrary and synthetic
Touch
To ch and haptics: 15
# Exploit our natural ability to ‘handle’ objects

16. THANK YOU
SEE YOU NEXT CLASS
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AND
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DON T
DON’T FORGET TO
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FINISH YOUR
HOMEWORK
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