The Perception of Data ' all in the minds eye

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The Perception of Data . all in the minds eye

• Janice Webster
• Director
• Virtual Reality Centre
• University of Teesside
• Middlesbrough TS1 3BA UK
• tel [phone]
• fax [phone]
• email j.webster_at_tees.ac.uk
• webvr.tees.ac.uk

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. without light the world would be dark and
mysterious

• Introduction
• Light human vision
• Colour response - colour spaces
• Text data graphics
• Visualisation and virtual reality
• 5 Summary conclusion

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1 Light human vision

• Phenomena of colour
• observer looks at light source
• observer sees light through a filter or projected
• observer sees light reflected from on object

.. but as we know. colour is all in the
minds eye
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Visible form of electromagnetic radiation - LIGHT

• visible light

350nm
760nm
violet blue cyan green yellow
orange red
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Newtons colour wheel . 1666by cagw 2000
Newton joined up the spectrum into a wheel and
placed white at the centre, the additive mix of
the spectral colours. Today, this is so
familiar!
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Thomas Young experiment1801

• green blue/violet cyan
• blue/violet red magenta
• red green yellow
• RGB(V) WHITE

NOTE light is only 1 octave, sound is 9 octaves
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Spectral power distribution

• Different light sources have very different
  colour rendering properties
• northlight - perceived as a good colour
  renderer, at 7500 Kelvin
• tungsten renders colours warm, at 2500 Kelvin
• white fluorescent renders green and blue/violet
  well at 3500 Kelvin
• computer graphics monitors are normally set up
  blue at 9300 Kelvin

Edwin Land the eye is able to see colour
independently of wavelength - I call it colour
constancy ref E Land, Experiments in
Colour Vision, Scientific American, 1959
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Mach-band effect Craik-Cornsweet experiment

• Mach-band effect is due to lateral inhibition.
  The eye perceives a lighter patch nearer to the
  darker boundary.
• Craik-Cornsweet effect demonstrates the
  importance of edge information.

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Simultaneous Contrast

• the change in appearance of a central area
  caused by the presence of a neighbouring area,
  especially when the target is completely
  surrounded both colour and size can appear to
  change

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Hue induction

• the presence of a surrounding colour
  relatively small amounts of another colour can
  cause an apparent colour change

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Constancy phenomena

• Results from automatic compensation by the
  visual system for variations in distance, angle,
  illumination and spectral content of the
  illumination.
• size - objects remain the same as distance
  increases
• shape - if given perspective prompts we can
  interpret ellipses as circles, rhomboids as
  squares
• lightness - we compare lightness levels, not
  absolute levels, so objects look comparatively
  dark or light
• colour - allows us to judge colours to be the
  same with different lighting conditions. A bonus
  for working in different locations. Ref Edwin Land

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Colour blindness

• Protanopes cannot see the long-wave lengths of
  red to reddish/orange
• Deuteranopes cannot distinguish colours in the
  medium wave-lengths around green
• Trianopes cannot distinguish the blue/violets in
  the short-wave region
• It is rare for people to have more than one
  type of special vision - not a defect!

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Illusions/1Chromatic aberration
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Illusions/2Relative size
isometric, false scale?
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2 Colour response, colour space

• We associate colours by the world around us
  and by the seasons.
• Spring - yellows, yellow-greens, light pinks
• Summer - vivid greens, reds, golden yellow
• Autumn - orange/brown/russets, faded green
• Winter - white, black, greys, pastels
• blue sea purple moor-lands, etc

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Colour spaces

• Isaac Newton left us with the legacy of the
  colour wheel - 1666
• Albert Munsell devised perhaps the best known
  colour model - 1905
• CIE system offers standardisation under specific
  viewing conditions - an Industry standard
  (Commission International de lEclairage)
• Alvey Ray developed the HSV (Hue, Saturation,
  Value) colour space model - 1978
• Gerald Munch created a similar model,
  substituting Value with Lightness, HLS - 1978

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Computer graphics colour space - Hue, Saturation,
Value (HSV)

• Alvey Ray based his colour model on the way
  that artists describe and mix colours, hue
  different lightness values.
• white (v1.00) 100
• yellow 90
• cyan 70
• green 60
• magenta 40
• red 30
• blue 10
• black (v0.00) 0
• .

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3 Text data graphics guidelines

• To effectively communicate our
  data/information we need to pay attention to
  finely detailed data graphics and text.

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Acuity of the eye for detail

• The acuity of the eye for detail is much
  higher where lightness change is involved this
  takes precedence over hue and saturation.

Remember the Mach banding and Craik-Cornsweet
diagrams.
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Lands experiments

• Edwin Land demonstrated that 90 of our
  knowledge is gained from SHAPE CONTRAST

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A reminder - the visual sensation of colour is
time dependant
If we stare at a bright image for too long we
can perceive after images If the world
moves too fast we get colour fusion, even
confusion!
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4 Visualisation and virtual reality

• Computer graphics has given us the ability to
  present sequences of data in rapid succession
• 3D displays can give greater insight into
  multi-dimensional data
• Real-time can aid our understanding especially
  when VR is immersive

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Virtual environments- why do they work?

• the user perceives reality by making use of
  their own cognitive maps
• the minds eye can interpret reality from a
  virtual model made of lines and digital textures
• VR systems provide visual immersion and real-time
  interaction

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Virtual environments in the minds eye

• we work out what is there, irrespective of hue,
  saturation and lightness
• we can feel movement even when our seats are
  stationary
• our brain can compute our own real-world from the
  computer generated VR world
• THUS we can present data and concepts
  effectively
• HOWEVER we can create what does not exist!

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5 Summary and conclusion

• human colour vision has been presented by
  reference to many standard experiments by the
  grand masters
• through our minds eye we have visualised some of
  the fundamental concepts about the human colour
  vision
• in data visualisation I recommended that the
  basic guidelines should be followed
• however, we still have much to learn in how
  better to use computer graphics to enhance visual
  awareness.and our power to understand and invent