Envelope of Discrepancy in Orthodontics: Enhancing Precision in Treatment
얼굴검출기법 감성언어인식기법
1. Part I: 얼굴 검출 기법 Part II: 감성 언어 인식 기법 2011. 3. 11( 금 ). 김성호 영남대학교 전자공학과 Brown Bag Seminar
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3. Proposed Object Representation Scheme Viewpoint Figure/Ground mask Local appearance For 2D object: (object center, scale) For 3D object: 3D object pose Boundary shape Figure/ground information Appearance codebook Part pose Joint appearance and shape model
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5. Mathematical Formulation for Categorization (1/2) Solution: C ategory label, V iewpoint, M ask Key issue: difficult modeling of prior due to complex high dimensions Our approach appearance pose Utilize graphical model especially Directed graphical model (Bayesian Net) V M F A X {C,B} N Top-down Bottom-up Viewpoint Figure-ground Codebook index b2 f4 f5 b4 b5 b6 b3 f3 b1 f1 f2 V M F G {C,B}
6. Learning for Distributed Category Representation CC: Category specific Codebook for top-down inference UC: Universal Codebook for bottom-up inference … … … … … … Joint appearance and boundary with viewpoint Car Airplane Issue How to select optimal codebook (CB) for category representation? Previous constellation model: fixed no. of parts Cannot handle large variations Why distributed? To handle large intra class variations
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8. Entropy of Candidate Codebook Low entropy surface marking High entropy Semantic parts Finding : High entropy codebook in should be selected for surface marking reduction
9. Inference Flow related to Category Model Input … … … Car Airplane … background CB UCB CCB Car category Multi-modal viewpoint Multi-modal figure-ground mask Final result Category Model Part-whole context Part-part context (estimate weight) Dense feature Matching to UC Grouping (similarity & proximity) +