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Korea University Dept.of Industrial System & Information Engineering User Interface Lab Chapter 3 _ Object Recognition + 이병용.

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Presentation on theme: "Korea University Dept.of Industrial System & Information Engineering User Interface Lab Chapter 3 _ Object Recognition + 이병용."— Presentation transcript:

1 Korea University Dept.of Industrial System & Information Engineering User Interface Lab Chapter 3 _ Object Recognition + 이병용

2 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 2 Gestaltist appoach Law of Pragnanz “of several geometrically possible organisation that one will actually occur which possess the best, simplest and most stable shape “ (Koffka, 1935) Perceptual Organization

3 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 3 e Gestaltist appoach - a. the law of proximity - b. the law of similarity - c. the law of continuation - d. the law of closure - e. the law of common fate ab c d Perceptual Organization

4 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 4 Gestaltist approach - figure- ground segregation - a) Homogeneous display b) Heterogeneous display - grouping of perceptual elements occurs early in visual processing Perceptual Organization

5 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 5 Gestaltist approach – Contrary evidence Perceptual Organization a b c UprightUpside down

6 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 6 Primal sketch : this provide a 2-dimensional description of the main light – intensity change in the visual input, including 2 ½ - D Sketch : this incorporate a description of the depth and orientation of visible surface, making use of information provided by hading texture, motion, binocular disparity, and so on 3 - D Model representation : 3 – dimensionally the way that is independent of objects and their relative positions in a way that is independent of the observer’s view point Theories of Objection Recognition Marr’s computational theory

7 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 7 Theories of Objection Recognition Biederman’s recognition by components theory - consisting of basic shape or components known as “geon” (36 개 )

8 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 8 Theories of Objection Recognition

9 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 9 Theories of Objection Recognition Five invariant properties of edges - culvature – point on a curve - parallel – sets of points in parallel - cotermination – edges terminating at a common point - symmety - versus asymmetry - collinearity – points sharing a common line

10 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 10 Objection Recognition Viewpoint _ dependent & viewpoint _ invariant theories - viewpoint invariant theory ease of object recognition is not affect by observer’s view point - viewpoint dependent theory change in viewpoint reduce the speed and of accuracy of object recognition

11 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 11 Brain System in Object Recognition Visual agnosia - Apperceptive agnosia object recognition is impaired because of deficits in perceptual processing - Associative agnosia Perceptual processes are essentially intact object recogntion is impaired partly or mainly

12 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 12 Brain System in Object Recognition

13 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 13 Brain System in Object Recognition

14 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 14 Face Recognition Bruce and Young’s model -Structural encoding -Expression anaysis -Facial speech analysis -Directed visual processing -Face recognition unit -Person identify nodes -Name generation -Cognitive system

15 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 15 Face Recognition Interactive activation and competition model WRUs = word recognition Units FRUs = face recognition Units NRUs = name recognition Unit s PRUs = Person recognition nodes WRUs = semantic information Unit

16 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 16 Face Recognition Are faces special ? Yes! - something special about face recognition 1) Holistic analysis 2) Analysis by parts Are faces special ? No! - why face appear special ?

17 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 17 Visual imagery “Seeing with the mind eye” -Mental imagery has been that it is very similar to perception -Why do we not confuse images and perception? Mental scanning - mental rotation

18 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 18 Thank You

19 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 19

20 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 20

21 Korea University Dept.of Industrial System & Information Engineering User Interface Lab View page 21


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