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Perception

Perception. Question of the Day. Why is recognizing an object so easy for humans, but so difficult for computers?. Perception: attaching meaning to incoming sensory information. What is this?. Figure 2-1 Distal Stimuli , Proximal Stimuli , and Percepts.

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Perception

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  1. Perception

  2. Question of the Day • Why is recognizing an object so easy for humans, but so difficult for computers?

  3. Perception: attaching meaning to incoming sensory information What is this?

  4. Figure 2-1Distal Stimuli, Proximal Stimuli, and Percepts.

  5. Gestalt ApproachFigureGround Figure 2-2

  6. Gestalt ApproachSubjectiveContoursFigure 2-3

  7. Gestalt principles of Perceptual Organization • http://www.aber.ac.uk • Proximity

  8. Gestalt principles of Perceptual Organization • Similarity • http://www.aber.ac.uk

  9. not this what most people would see Gestalt principles of Perceptual Organization • Good continuation • http://www.aber.ac.uk

  10. Gestalt principles of Perceptual Organization • Closure http://daphne.palomar.edu

  11. Gestalt principles of Perceptual Organization • Common fate

  12. Figure 2-5 Gestalt principles of Perceptual Organization

  13. Bottom-Up Processes The number “4” from the check is compared to a list of stored templates. Template matching

  14. Bottom-Up Processes Problems with Template Matching • Large number of stored templates needed • How are new templates made? • An object can be “more or less” like the template • We can recognize many variations of a template

  15. Bottom-Up Processes Figure 2-8

  16. Bottom-Up Processes Featural Analysis features (“parts”) of a stimulus are recognized by feature detectors and added together to help us perceive an object • Lines or edges • Geons • Phonemes • Parts of a face (eyes, nose…)

  17. Featural Analysis Geons

  18. Figure 2-14 A depiction of Selfridge’s (1959) Pandemonium model. Featural Analysis Letter detection

  19. Bottom-Up Processes Featural Analysis Feature Properties • Detectors can respond at different intensities • Connections between detectors can have different strengths • It is possible to change what a detector will respond to

  20. Bottom-Up Processes Prototype Matching

  21. Bottom-Up Processes Prototype Matching http://www.palm.com

  22. Top-Down Processes Figure 2-19An example of context effects in perception.

  23. Top-Down Processes • Perceptual Learning • Change Blindness • Word Superiority Effect 1 2a 2b Sad Bad OR S OR OR Sgf Bgf OR

  24. Bottom-Up and Top-Down Processing working together a t Word Perception • Connectionist Model Words Bat Letters B Fox Bat Fat Features (lines) I Rat Cat Input

  25. Figure 2-24 (p. 73)Example of stimuli used in the PET scan study of processing words. See text for explanation. Word Perception • Neuropsychological Perspective

  26. Figure 2-30 Examples of how contour information influences recognition in persons with apperceptive agnosia. (A) Patients with apperceptive agnosia have difficulty recognizing this object as a chair because they cannot interpolate the missing contours. (B) Patients with apperceptive agnosia would have difficulty recognizing the chair when it is viewed from this unusual angle. Agnosia

  27. Question of the Day • Why is recognizing an object so easy for humans, but so difficult for computers? • Stimulus ambiguous • Objects overlap • Parts of objects may be hidden • Differences in lightness/darkness could be from more than one cause

  28. Outline • Introduction • Gestalt perceptual principles • Bottom-up processing • Template matching • Featural analysis • Prototype matching • Top-down processing • Agnosia

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