CS223B-L8-OpticalFlow

CS223B-L8-OpticalFlow - Stanford CS223B Computer Vision,...

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Sebastian Thrun CS223B Computer Vision, Winter 2009 Stanford CS223B Computer Vision, Winter 2008/09 Lecture 8 Optical Flow Professor Sebastian Thrun CAs: Ethan Dreyfuss, Young Min Kim, Alex Teichman
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Sebastian Thrun CS223B Computer Vision, Winter 2009 2 Optical Flow: Outline Examples Formal definition, 1D case From 1D to 2D: Aperture Problem Course motion and pyramids
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Stereo versus Optical Flow Stereo: 2 or more images taken at same point in time, from different vantage points Optical Flow: 2 or more images taken one after another Objects in scene may move Camera may move (but motion unknown) Goal of optical flow: track features/objects
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Image sequence (single camera) Tracked sequence 3D structure + 3D trajectory Image tracking 3D computation Courtesy of Jean-Yves Bouguet
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow David Stavens, Andrew Lookingbill, David Lieb (CS223B 2004)
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Image sequence (single camera) Tracked sequence Image tracking 3D computation Courtesy of Jean-Yves Bouguet
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow (+Structure From Motion) 3D structure + 3D trajectory Courtesy of Jean-Yves Bouguet
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Sebastian Thrun CS223B Computer Vision, Winter 2009 * From Marc Pollefeys COMP 256 2003 Optical Flow Break Down? Perhaps an aperture problem discussed later. Perhaps an aperture problem discussed later.
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Sebastian Thrun CS223B Computer Vision, Winter 2009 9
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow: Outline Examples Formal definition and assumptions Optical Flow: 1D case From 1D to 2D: Aperture Problem Course motion and pyramids
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Sebastian Thrun CS223B Computer Vision, Winter 2009 ) 1 ( + t I What is Optical Flow? Optical Flow } { ), ( i p t I 1 p 2 p 3 p 4 p 1 v 2 v 3 v 4 v } { i v Velocity vectors Velocity vectors Common assumption: Common assumption: The appearance of the image patches do not change (brightness constancy) ) 1 , ( ) , ( + + = t v p I t p I i i i
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Assumptions Brightness Constancy Spatial Coherence Temporal Persistence
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Assumptions: Brightness Constancy * Slide from Michael Black, CS143 2003
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Assumptions: * Slide from Michael Black, CS143 2003
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow Assumptions: * Slide from Michael Black, CS143 2003
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow: Outline Examples Formal definition and assumptions Optical Flow: 1D case From 1D to 2D: Aperture Problem Course motion and pyramids
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Sebastian Thrun CS223B Computer Vision, Winter 2009 Optical Flow: 1D Case
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CS223B-L8-OpticalFlow - Stanford CS223B Computer Vision,...

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