lecture21 - EECS 442 Computer vision Object Recognition...

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EECS 442 – Computer vision Object Recognition Intro Recognition of 3D objects Recognition of object categories: Bag of world models Part based models 3D object categorization Faces Segments of this lectures are courtesy of Prof A. Torralba, R. Fergus and F. Li Recognizing and Learning Object Categories: Year 2007
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Challenges: intra-class variation
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Usual Challenges: Variability due to: View point Illumination Occlusions
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Problem with bag-of-words All have equal probability for bag-of-words methods Location information is important
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Part Based Representation Object as set of parts Model: Relative locations between parts Appearance of part Figure from [Fischler & Elschlager 73]
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History of Parts and Structure approaches Fischler & Elschlager 1973 Yuille ‘91 Brunelli & Poggio ‘93 Lades, v.d. Malsburg et al. ‘93 Cootes, Lanitis, Taylor et al. ‘95 Amit & Geman ‘95, ‘99 Perona et al. ‘95, ‘96, ’98, ’00, ’03, ‘04, ’05 Ullman et al. 02 Felzenszwalb & Huttenlocher ’00, ’04 Crandall & Huttenlocher ’05, ’06 Leibe & Schiele ’03, ’04 Many papers since 2000
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A B D C Deformations
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