Visual Perception Flashcards
Preattentive processing
Preattentive processing of visual information is performed automatically on the entire visual field
- quickly, effortlessly and in parallel
- without focusing on visual attention
When is visual information processing is called preattentive?
Visual information processing is called preattentive, when information is gained in less than 200-250ms
- less time than would be needed to move the eyes
- using peripheral vision
In human vision, preattentive processing is the mechanism that lets us notice events in…
Visual periphery (perimeter of a circler)
- Drawing our attention
- Directing foveal vision
In visual design, we can apply knowledge of preattentive processing to
- to direct attention to critical information
- to convey information “at a glance”
Preattentive features (Pop-out features)
Preattentive features (also called out pop out features) are visual properties that can be perceived without focused attention
Pop-out features
- Some features pop out more than others
- Motion, Colour
- Some features convey quantitative information “at a glance”, e.g.
- How long
- How big
- At which position
- In which direction
Preattentive Processing - Key Points
- Preattentive processing supports the exploration and discovery of information in the visual field
- Highly parallel processing in the visual
periphery - Faster than we can move our eyes for
focused attention
- Highly parallel processing in the visual
- Preattentive processing is fundamental to information visualization
- Pop-up features can be used to convey
information efficiently - Without focused attention
- Without cognitive effort
- Pop-up features can be used to convey
Gestalt Perception
- Human vision is biased to perceive structure
- Whole shapes, figures and objects
- Gestalt
- Pattern, configuration
- Essence or shape of an entity’s complete form
- A unified whole
- Given a visual image, the human brain chooses
- The simplest interpretation
- WIth the most symmetry
Gestalt Principles in Design
- Gestalt principles that are found in design guidelines
- In Gestalt perception, there are further principles
- common fate
- Symmetry
- Figure/ground
Perception of relationships
- Principles of Proximity, Similarity, Enclosure, Connection are about perception of groups and relationships
- Effective communicate of what belongs together
- User interface layout
- Information visualization
- Visual structure of documents
Perception of objects
Principles of closure, continuity and symmetry are about the perception of objects as a whole – resolving ambiguity in what we see.
- Closure: seeing the whole even when only parts are visible
- Continuity: seeing the whole even if partly occluded
- Symmetry: choose an interpretation that has the highest symmetry
Perception of figure/ground
The principle of figure/ground is about what we perceive to be in the foreground (the figure) versus the background (ground)
- The brain simplifies a visual scene by deciding what is in the foreground
- Important as the figure gets the primary attention
- Separation supported by strong contrast
- Light/dark, Crisp/blurry, Saturated/grey
- Smaller, crisper, brighter objects perceived in front
Visual Structure
- Visual structure helps scan and understand information more quickly
- The two screens have the same amount and density of information
- But spacing and grouping of characters supports faster search
- Structure and representation matter
- Same information
- Less cognitive effort
Gestalt and Structure - Key Points
Gestalt principles describe how we see structure in all of the visual stimuli that we receive
- Perception of the whole even if it is not complete; of groups and relationships; and of foreground versus background
- In design, Gestalt principles guide the layout of user interfaces and information, to effectively communicate structure
- Visual structure, hierarchy and spacing reduce effort and time for visual search
Visual Encoding
How do we perceive data in information visualisation?
- Visual encodings make use of different perceptual channels for representing data
- Length, Area, Position, Colour, Shape, …
- Some encodings are more effective than others
e.g., length > area for comparing size - Depending on the type of data
- Quantitative, ordinal, categorical