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Cognitive Processes PSY 334. Chapter 2 – Perception June 30, 2003. Visual Perception. Distal stimulus -- tree Proximal stimulus – image of tree on retina Percept – interpretation of proximal stimulus as a tree Size and color constancy. Information Coding.
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Cognitive ProcessesPSY 334 Chapter 2 – Perception June 30, 2003
Visual Perception • Distal stimulus -- tree • Proximal stimulus – image of tree on retina • Percept – interpretation of proximal stimulus as a tree • Size and color constancy
Information Coding • On-off cells in LGN feed into edge and bar detectors in the visual cortex. • Edge detectors – respond positively to light on one side of a line, negatively on the other side of the line. • Bar detectors – responds maximally to a bar of light covering its center.
Marr • Depth cues (texture gradient, stereopsis) – where are edges in space? • How are visual cues combined to form an image with depth? • 2-1/2 D sketch – identifies where visual features are in relation to observer. • 3-D model – refers to the representation of the objects in a scene.
Pattern Recognition • Classification and recognition occurs through processes of pattern recognition. • Bottom-up processes – feature detection • Top-down processes -- conceptually driven processing
Object Recognition • Two stages: • Early phase – shapes and objects are extracted from background. • Later phase – shapes and objects are categorized, recognized, named.
Disruptions of Perception • Visual agnosias – impairment of ability to recognize objects. • Demonstrate that shape extraction and shape recognition are separate processes. • Apperceptive agnosia (lateral) – problems with early processing (shape extraction). • Associative agnosia (bilateral) – problems with later processing (recognition). • Prosopagnosia – visual agnosia for faces.
Gestalt Priniciples • Wertheimer, Koffka, Kohler. • Form perception – segregation of a display into objects and background. • Principles of perceptual organization allow us to see “wholes” (gestalts) formed of parts. • We do not recognize objects by identifying individual features.
Five Principles • Proximity • Similarity • Good continuation • Closure • Common fate • Elements that move together group together.
Examples • Gestalt principles of organization • Reversible figures
Law of Pragnanz • Of all the possible interpretations, we will select the one that yields the simplest or most stable form. • Simple, symmetrical forms are seen more easily. • In compound letters, the larger figure dominates the smaller ones.
Visual Illusions • Depend on experience. • Influenced by culture. • Illustrate normal perceptual processes. • These are not errors but rather failures of perception in unusual situations.
Visual Pattern Recognition • Bottom-up approaches: • Template-matching • Feature analysis • Recognition by components
Template-Matching • A retinal image of an object is compared directly to stored patterns (templates). • The object is recognized as the template that gives the best match. • Used by computers to recognize patterns. • Evidence shows human recognition is more flexible than template-matching: • Size, place, orientation, shape, blurred or broken (ambiguous or degraded items easily recognized by people.
Feature Analysis • Stimuli are combinations of elemental features. • Features are recognized and combined. • Features are like output of edge detectors. • Features are simpler, so problems of orientation, size, etc., can be solved. • Relationships among features are specified to define the pattern.
Evidence for Feature Analysis • Confusions – people make more errors when letters presented at brief intervals contain similar features: • G misclassified: as C (21), as O (6), as B (1), as 9 (1) • When a retinal image is held constant, the parts of the object disappear: • Whole features disappear. • The remaining parts form new patterns.
Object Recognition • Biederman’s recognition-by-components: • Parts of the larger object are recognized as subobjects. • Subobjects are categorized into types of geons – geometric ions. • The larger object is recognized as a pattern formed by combining geons. • Only edges are needed to recognize geons.
Tests of Biederman’s Theory • Object recognition should be mediated by recognition of object components. • Two types of degraded figures presented for brief intervals: • Components (geons) missing • Line segments missing • At fast intervals (65-100 ms) subjects could not recognize components when segments were missing.