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Transcript of 11 4a Human Intro-Sensory Dix1
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The Human
Introduction, Modeling, Vision
Human Computer Interaction, 2 nd Ed.
Dix, Finlay, Abowd, and BealeChapter 1
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Introduction
� About HCI and humans «
� Interaction captured in figurebelow with ³system, task,user´ ± So far, have talked about
³interface design´ of system� Guidelines, principles,
evaluation, etc.
� Now will look at user
± Will consider ³model´ of human
± Models capture elements of whatever is being modeledthat are relevant to someendeavor
� E.g., ³cognitive engineering´Task
System
User ³feedback´and its representation
(possibly manipulable)
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Introduction
� On describing humans ± To understate, a question of long standing «
� One of the big questions «
± Has and can be done in various ways and at different levels of analysis� Moral, spiritual, «., psychological, « physiological, « chemical
� Reductionist
� Psychology focuses on the individual
� Many orientations through psychology¶s short history ± Note: Clinical/personality orientations, e.g., Freud, Jung, have their own utility in
explanation, but are rarely subject to scientific investigation
± Structural, turn of 20th
century, relations among elements ± Gestalt, 1930¶s and on, general, especially of perception, still useful
± Behaviorist, all S->R, which is fine for some things, but fall short for explanationof mental phenomena
± Information processing/Cognitive, current orientation� Influences from Shannon¶s ideas on information, shortcomings of behaviorism,
successes in codifying information in computing
� ³Human information processor´
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Modeling Humans
� Any theory or model is an abstraction
� For HCI, goals are primarily in ³Computer´ and ³Interaction´ ± Utility of human model lies in how well it helps with interfaces
� Card, Moran, and Newell (1983) M odel Human Processor ± ³Classic´ example of cognitive architecture with focus on humans interacting with
computers
± Perceptual system, motor system, cognitive system
± Each has own processor and memory
± Principles of operation dictate system behavior under
certain conditions
± A very simple model
� Dix et. al use similar information processing
division of elements in chapter
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Overview
� Dix et al. model: ± Information i/o «
� visual, auditory, haptic, movement
± Information stored in memory
� sensory, short-term, long-term
± Information processed and applied� reasoning, problem solving, skill, error
� Idea tonight ± Give broad overview of elements of human
± Show that for some elements of user interface design, detailed knowledge is atleast useful and perhaps critical
� For design - sensory, perceptual, and cognitive guidelines andprinciples
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Some Terminology
� Transduction of
energy, etc. by
sensory receptors ± Light to neural
impulses by retinalcells
Sensation Perception Cognition
� Latin ±� cognitio ± knowledge
� ³Higher level´ mental
representations and
procedures
� Process of thought
� Forming a ³mental
image´ or
awareness and
representation� To ³see a window´
� Top down andbottom up
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Demo
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Demo
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Model Human Processor + Attention
� A ³useful big picture - Card et al. ¶83 plus attention ± Senses/inputp f(attention, processing)p motor/output
± Notion of ³processors´� Purely an engineering abstraction
� Detail next slide ± And in lectures!
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Model Human Processor - Original
� Card et al. ¶83
� An architecturewithparameters for cognitiveengineering «
± Will see visual image store, etc.tonight
� Memory properties ± Decay time: how long memory lasts
± Size: number of things stored
± Encoding: type of things stored
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Model Human Processor - Original
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Dix: Information Input and Output
� Again, human consideredas information processor
� Input channels are thefive senses ± With some more important
than others
± Vision primarily
� Output channels arehuman effectors ± E.g., limbs, fingers, head,
vocal system
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Vision
� Vision and visual perception studied across arange of disciplines
� Points tonight meant to highlight usefulness for HCI in knowing about vision
� For vision consider (Dix): ± Physical reception of stimulus
± Processing and interpretation of stimulus
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The Eye - Physical Reception
� Mechanism for receiving light andtransforming it into nervetransmissions
± A transducer: light -> nerves
� Light reflects from objects ± Some strikes retina
± Images are focused upside-down onretina
� Ganglion cells (brain!) detect patternand movement
� As camera has ± equivalent of lens, aperture (pupil)
± and film (retina)
� Note that image is upside down onretina!
± « perception
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Environment: Visible Light
� Generally, the body¶s sensorysystem is the way it is because ithad survival value ± Led to success
� survival and reproduction
� Focus on human vision (because of computer), but all share basicnotions
� Humans have receptors for (asmall part of) theelectromagnetic spectrum
± Have receptors sensitive to (firewhen excited by) energy 400-700nm
± Snakes ³see´ infrared, someinsects ultraviolet
� i.e., have receptors that fire
± What would life be like if humanscould see other parts of
electromagnetic spectrum???
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Human Eye: Retinal Receptors
� Two types of (photo) receptors on retina: rods and cones ± Rods look like, well, rods «
± Will later look at color blindness « when cones fail
� Rods: ± spread all over the retinal surface (75 - 150 million)
± low resolution, no color vision, but very sensitive to low light (scotopic or dim-light vision)
� Cones: ± dense array around central portion of retina - fovea centralis (6 - 7 million)
± high-resolution, color vision, but require brighter light ( photopic or bright-light vision)
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Human Eye: Lens
� Eye has compound lens:
± cornea (power) and lens (adjust focal length)f = focal length of lens
d = distance to object
r = distance to image that is formed
± Flexibility of lens changes with age, approaching 0 at 60 years
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Human Eye: Depth of Field and Focus
� Depth of focus ±will see interesting affect «
± Distance over which objects are in focus without change in focus
� Note: Different colors have different depths of focus ± chromatic aberration
± Varies with size of pupil ± Range of focus:
Distance Near Far Depth of focus50 cm 43 cm 60 cm 17 cm
1 m 75 cm 1.5 m 75 cm
2 m 1.2m 6.0m 1.8 m
3 m 1.5m Infinity Large
± Rarely do computer systems model
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Human Eye: Depth of Field - Example
� Photographic Images:
± Depth of field longer with small aperture(f stop)
± Range of focus:
Distance Near Far Depth of focus50 cm 43 cm 60 cm 17 cm
1 m 75 cm 1.5 m 75 cm
2 m 1.2m 6.0m 1.8 m
3 m 1.5m Infinity Large
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Human Eye: Chromatic Aberration
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Human Eye: Chromatic Aberration
� Different wavelengths of light focus
at different distances within eye
± Short-wavelength blue light refracted
more than long-wavelength red light
± Focusing on a red patch, an adjacent
blue patch will be significantly out of focus
� Strong illusory depth effects
�H
uman eye has no correction for chromatic aberration!
± Inadvisable: fine blue patterns in
visualizations!
± Visual effects in soap bubbles, crystal
sculptures, etc.
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Using Physiology for Design
� Chromatic Aberration
� Different wavelengths focus differently
± Highly separated wavelengths (red & blue) can¶t be focused simultaneously
� Guideline: Don¶t use red-on-blue text
± It looks fuzzy and hurts to read
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FYI: Human Eye: Receptors
� Lens focuses image onmosaic of photoreceptor cells lining retina
� From 1 ± 100 receptorsfeed into 1 ganglion cell
� Fovea
± Small area in center of retina densely packed withcones
± Vision sharpest
± ½o
- 2o
of arc
Receptor mosaic in fovea
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Interpreting the Visual Signal
� Size and depth
± V isual angle indicates how much of view object occupies(relates to size and distance from eye)
� V isual acuity is ability to perceive detail (limited)
± familiar objects perceived as constant size(in spite of changes in visual angle when far away)
± cues like overlapping help perception of size and depth
� Brightness
± Human system not map directly to physical
� C olor
± Different sensory elements responsible for perception of color
± Implications for color use, e.g., color blindness
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Human Eye: Visual Angle
� Visual angle - angle subtended by object at eye of viewer
± In degrees, minutes, seconds of arc
± Thumbnail at arm¶s length subtends ~1o
of visual angle
± 1cm (2/5´) object at 57 cm (20´), monitor distance, ~1o
of visual angle
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FYI:
Human Eye: Acuities - Grating Acuity
� Acuities ± Measurements of abilities to
see detail
± Provide ultimate limits of information densities canperceive
� Resolve to about 1 min. of arc ± Roughly corresponds to with
receptor spacing in fovea
± E.g., to see 2 lines as distinctblank space between should lie onreceptor
± So, should be able to perceive
lines separated by twice receptor spacing
� Superacuities ± Resolution above what expected
by receptor density due tointegration of signals
GratingAcuity- 1-2 minutes of arc
- Ability to distinguish a
pattern of bright and dark
bars from a uniform gray
background
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FYI:
Acuities: Point, Letter, Stereo, Vernier
� Point acuity ± 1 minute of arc
± Ability to resolve two distinct pointtargets
� Letter acuity
± 5 minute of arc ± Ability to resolve letters
± Snellen eye chart� 20/20 means a 5-minute letter target
can be seen 90% of time
� Stereo acuity
± 10 seconds of arc ± Ability to resolve objects in depth
± Measured as difference between 2angles (a and b) for a just-detectabledifference
� Vernier acuity
± 10 seconds of arc ± Ability to see if two lines are collinear
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FYI:
Acuity Distribution and Visual Field� Again, receptors densely
packed at fovea
� Binocular overlap ± Region of visual field viewed by
both eyes
± Only here, stereopsis
� Visual acuity non-uniformlydistributed over visual field ± E.g., Can resolve only about 1/5
detail at 10o
� Next slide (tries) demonstrate³equi-resolvability´ of charactersas a function of distance fromfovea ± r = f(dist. fovea)
± (stare at center and see smaller characters at center as well or better than those at periphery)
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Human Eye: Resolution
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FYI:
Brightness, Luminance, Lightness� Brightness
± subjective reaction to levels of light
± affected by luminance of object
± measured by just noticeable difference
± Ecologically, need to be able to manipulate objects in environment
� Information about quantity of light, of relatively little use
± Rather, what need to know about its use
� Human visual system evolved to extract surface properties
± Loose information about quantity and quality of light ± E.g., experience colored objects, not color light
� Color constancy
± Similarly, overall reflectance of a surface
� Lightness constancy
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FYI:
Luminance, Brightness, Lightness
� Luminance ± Amount of light (energy) coming from region of space,
� Measured as units energy / unit area
� E.g., foot-candles / square ft, candelas / square m
� Physical
� Brightness
± Perceived amount of light coming from a source ± Here, will refer to things perceived as self-luminous
� Lightness ± Perceived reflectance of a surface
± E.g., white surface is light, black surface is dark
� Again, ± Physical - Luminance
± Number of photons coming from a region of space
± Perceptual - Brightness ± Amount of light coming from a glowing source
� Lightness ± Reflectance of a surface, paint shade
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FYI:
Brightness� Perceived amount of light coming from a glowing (self-luminous) object
± E.g., instruments
� Perceived brightness very non-linear function of the amount of light ± Shine a light of some intensity on a surface, and ask an observer, ³How bright?´
Intensity = How bright is the point?´
1 1
4 2
16 4
� Stevens power law ± Perceived sensation, S, is proportional to the stimulus intensity, I, raised to a power, n
± S = I n
± Here, Brightness = Luminancen
± With n = 0.333 for patches of light, 0.5 for points ± Applies only to lights in relative isolation in dark, so application more complicated
� Applies to many other perceptual channels ± Loudness (dB), smell, taste, heaviness, force, friction, touch, etc.
� Enables high sensitivity at low levels without saturation at high levels
� Just-noticeable difference depends on value
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Dix: Interpreting the Signal - Color
� Color ± made up of hue, intensity, saturation
± cones sensitive to colour wavelengths ± blue acuity is lowest
± ~8% males and ~1% females color blind
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Trichromacy Theory
� Recall, that there are 2 types
of retinal receptors:
± Rods, low light, monochrome
� So overstimulated at all but low
levels contribute little
� So only consider cones for color
vision
± Cones, high light, color
± Not evenly distributed on retina
Distribution of receptors across the retina, left eyeshown; the cones are concentrated in the fovea,
which is ringed by a dense concentration of rods
http://www.handprint.com/HP/WCL/color1.html#oppmodel
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Trichromacy Theory
� Cones (3 types) differentially sensitive towavelengths ± ³trichromacy´
� Each type cone has different peak sensitivity: ± S: 450 nm ³blue´
± M: 540 nm ³green ± L: 580 nm ³red´
± More later
± No accident 3 colors in monitor
� Color space: ± An arrangement of colors in a 3-dimensional
space� Monitor: R,G,B� Primary paint colors: R,Y,B� Printer: cyan, magenta, yellow
± There are many, each designed for differentpurposes
± Will consider several
± Can match all colors perceived with 3 colors� Does not matter that spectral composition of that
patch of light may be completely different
± But, chickens have 12 « ± Different gamut, more later
Cone sensitivity functions
Cone response space, defined by
response of each of the three cone
types. Becomes 2d with color deficiency
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FYI:
Color Space Ex.: RGB Color Cube
� Again, can specify color with 3 ± Will see other way
� RGB Color Cube ± Neutral Gradient Line
± Edge of Saturated Hues
± ppt example
http://graphics.csail.mit.edu/classes/6.837/F01/Lecture02/
http://www.photo.net/photo/edscott/vis00020.htm
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Cone Sensitivity Functions
� Cone receptors least sensitive to(least output for) to blue
Relative sensitivity curves for the three types of
cones, log vertical scale, cone spectral curves from
Vos & Walraven, 1974
Relative sensitivity curves for the three
types of cones, the Vos & Walraven
curves on a normal vertical scale
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Color Blindness
� ~9% male, and ~1% females havesome form of color visiondeficiency!
� Most common:
± Lack of long wave length sensitivereceptors (red, protanopia)� See figure at right bottome
± Lack of mid wave length receptors(green, deuteranopia)
� Results in inability to distinguish redand green
� E.g., cherries in 1st
figure hard to see
� Trichromatic vs. dichromaticvision
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FYI: Perceived Color
� Color perceived relative to context ± Are the ³X´s in the figure below the same color?
± Easy implications for use in maps
� Contrast illusion
± An illusion is an extreme case
� Somewhat ³surprising´ because it leads to error
± Appears to be different color X!
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FYI: Perceived Color
� With color of x touching «
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FYI: Afterimage
� Occurs due to bleaching of photopigments
± (demo next slide)
� Implications for misperceiving(especially contiguous colors ±and black and white)
± ³I thought I saw «´
� To illustrate:
± Stare at + sign on left� May see colors around circle
± Move gaze to right
± See yellow and desaturatedred
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Afterimage Example
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Dix: Interpreting the signal (cont)
� The visual system compensates for:
± movement
± changes in luminance.
� Context is used to resolve ambiguity
� Optical illusions sometimes occur due to
over compensation
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FYI: Simultaneous Brightness Contrast
� Gray patch on a dark background looks lighter than the same patchon a light background ± Predicted by DOG model of concentric opponent receptive fields
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FYI: Mach Bands
� At pointwhere uniform area meets a luminance ramp, brightband is perceived ± Said another way, appear where abrupt change in first derivative of
brightness profile
± Simulated by DOG model
± Particularly a problem for uniformly shaded polygons in computer graphics� Hence, various methods of smoothing are applied
Ernst Mach
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Psychology and Design of
Interactive Systems� Some direct applications
± e.g. blue acuity is poor blue should not be used for important detail
� However, correct application generally requiresunderstanding of context in psychology, and anunderstanding of particular experimental conditions
� A lot of knowledge has been distilled in ± guidelines
± cognitive models
± experimental and analytic evaluation techniques
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End ?
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Optical Illusions
the Ponzo illusion the Mueller-Lyer illusion
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Optical Illusions
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Preattentive Processing and Illusions
� What is wrong with this
triangle?
± Impossible (or at least
difficult) to build
� Cues for perception
misleading
± Must rely on conscious
(rational) processesintelligence to figure it out,
± Conscious/rational
processes much slower
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The Other Senses «
� But not smell and taste ± Long latency, practical challenges
� Hearing
� Touch
� Kinesthetic ± Movement ± Fitt¶s law
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Hearing
� Provides information about environment:distances, directions, objects etc.
� Physical apparatus:
± outer ear ± protects inner and amplifies sound ± middle ear ± transmits sound waves asvibrations to inner ear
± inner ear ± chemical transmitters are releasedand cause impulses in auditory nerve
� Sound ± pitch ± sound frequency
± loudness ±amplitude
± timbre ± type or quality
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Hearing (cont)
� Humans can hear frequencies from 20Hz to15kHz ± less accurate distinguishing high frequencies than
low.
� Auditory system filters sounds ± can attend to sounds over background noise.
± for example, the cocktail party phenomenon.
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Touch
� Provides important feedback about environment
� May be key sense for someone who is visually impaired
� Stimulus received via receptors in the skin
± thermoreceptors ± heat and cold
± nociceptors ± pain
± mechanoreceptors ± pressure
(some instant, some continuous)
� Some areas more sensitive than others, e.g., fingers
� Kinethesis - awareness of body position
± affects comfort and performance.
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Movement
� Time taken to respond to stimulus:reaction time + movement time
� Movement time dependent on age, fitness etc.
� Reaction time - dependent on stimulus type: ± visual ~ 200ms
± auditory ~ 150 ms
± pain ~ 700ms
� Increasing reaction time decreases accuracy in theunskilled operator but not in the skilled operator.
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Movement ± Fitt¶s Law
� Fitts' Law, 1954 ±Fundamental law of human sensory-motor system
±Practical application in interface design
±Describes the time taken to hit a screen target
±Time, Mt, to move hand to a target of size, S, at distance, D, away
Mt = a + b log2(D/S + 1)
where: a and b are empirically determined constants
Mt is movement time
D is Distance
S is Size of target
± ³index of difficulty´: log2(D/S + 1)� Same performance at greater distance with greater size
targets as large as possible, distances as small as possible
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Fitt¶s Law ± Example Implication
� Hierarchical menus are hard to hit ± Especially when it takes two actions «
P h l d D i f
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Psychology and Design of
Interactive Systems� Some direct applications
± e.g. blue acuity is poor blue should not be used for important detail
� However, correct application generally requiresunderstanding of context in psychology, and anunderstanding of particular experimental conditions
� A lot of knowledge has been distilled in ± guidelines
± cognitive models
± experimental and analytic evaluation techniques
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End