Title: Psychophysical Image Quality Metrics
1Psychophysical Image Quality Metrics
- Ann McNamara
- Image Synthesis Group
- Trinity College, Dublin, Ireland
2Psychophysical Image Quality - Overview
- Realism
- Psychophysics
- Working with Participants
- Procedures for comparing Real Scenes
- with Synthetic Image
- Case Study A Psychophysical Investigation
3Need For Accuracy
- Lighting Engineering
- Architecture
- Stage Lighting
- Industry
- Entertainment
- Safety Critical
- Archaeology
4Why Compare Images ?
- Compare and validate lighting simulations
- Use comparisons to guide rendering
- more efficiently
- Can we compute less without altering human
perception of an image - While pixel by pixel comparison might be 0,
human might not see any difference
5Pixel by Pixel Comparison
6Visual Psychophysics
- Determine the relationship between the
physical world and humans subjective experience
of that world
7Visual Psychophysics
- Measure the mind
- Without bias
- Systematically
- Repeat Observations
- Relationship between mind matter
8Experimental Design
- Make inferences without ambiguity
- Rule out alternative causes, leaving only
- the actual factor that is the real cause
9Experimental Design
Plan
10Experimental Design
- Selecting what to study
- Selecting who to study
- Specifying how to study
- Specifying the sequence of
- measurements to be recorded
- What kind of evidence will result
11Order Effects
- Order of Presentation
- Good before Bad
- Timing
12Randomisation
- Not haphazard
- No event is ever predictable from
- any of the preceding sequence
13Counterbalancing
- Order of Presentation
- Influence Results
- Make Experiment fair
- Reduce Bias
14Control of Extraneous Variables
- May influence or affect the results of
- the condition
- For Example - Outside illumination
15Experimental Design
- The Question to be Answered
- Choice of Task (Measure)
- Choice Control of Physical Stimuli
- Organisation of Participants
- Sequence of Presentation
- Instructions to Participants
- Recording, Presenting Analysing Results
16Psychophysics for Judging Image Quality
- Psychophysical methods allow us to ask
- how close to reality computer images are
- Validate progressive global illumination
- solutions
17Case StudyComparing a real scene with computer
generated images that represent that scene
18A method of comparing real scenes with graphics
- Task Estimate the lightness of
- various regions of a scene
- Lightness perception is known
- to depend on prior perception of 3-D
- shape and illumination
19A method of comparing real scenes with graphics
- Lightness is therefore a useful measure
- of the fidelity of illumination and
- 3-D reconstruction of a graphics scene
20Why Lightness ?
21Physical Stimulii
22Physical StimuliThe Real Scene
- Painted 5-sided Cube
- Objects painted with different grey paints
- Complex illumination, with secondary
reflections
23Physical StimuliGraphic Reconstructions
24Participants and Sequencing
- How Many Participants
- Randomisation of Participants
- Randomisation of presentation
- Time of Day Influence
- Training on Physical Stimuli
25Physical StimuliTraining on Patches
26Physical StimuliTraining on Patches
27 Experiment
28Case Study Results
- Average match in each image is plotted
- along side average match in the real scene
29Real Photograph
30Real Two Ambient Bounce
31Real Eight Ambient Bounce
32Real Eight Ambient Bounce Bright
33Real Default
34Real Estimated Materials
35Real Estimated Illumination
36Real Tone Mapped
37Real Raytraced
38Real Radiosity
39Data Analysis
- Correlation - indication of how closely related
two sets of data are - ANOVA - Analysis Of Variance
- T Tests
- Statistics reinforce the evidence
- from the data
40Summary
- Experiments should be designed to
- produce accurate results
- Attention must be paid to a number of
- subtle experimental issues such as sample
- size, bias and randomisation
41Further Information
- HTTP//www.cs.tcd.ie/Ann.McNamara
- HTTP//www.isg.cs.tcd.ie/Campfire
- Birds of a Feather Perception and Graphics,
Monday 13th August, 1-2pm, Room 506
42Psychophysical Image Quality Metrics
- Ann McNamara
- Image Synthesis Group
- Trinity College, Dublin, Ireland