Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/412778
Title: Passive photometric stereo from motion
Authors: Lim, Jongwoo;Ho, Jeffrey;Yang, Ming Hsuan;Kriegman, David
subject: Science & Technology
Year: 2005
Abstract: We introduce an iterative algorithm for shape reconstruction from multiple images of a moving (Lambertian) object illuminated by distant (and possibly time varying) lighting. Starting with an initial piecewise linear surface, the algorithm iteratively estimates a new surface based on the previous surface estimate and the photometric information available from the input image sequence. During each iteration, standard photometric stereo techniques are applied to estimate the surface normals up to an unknown generalized bas-relief transform, and a new surface is computed by integrating the estimated normals. The algorithm essentially consists of a sequence of matrix factorizations (of intensity values) followed by minimization using gradient descent (integration of the normals). Conceptually, the algorithm admits a clear geometric interpretation, which is used to provide a qualitative analysis of the algorithm's convergence. Implementation-wise, it is straightforward being based on several established photometric stereo and structure from motion algorithms. We demonstrate experimentally the effectiveness of our algorithm using several videos of hand-held objects moving in front of a fixed light and camera
Description: 

URI: http://localhost/handle/Hannan/345996
http://localhost/handle/Hannan/412778
Appears in Collections:2002-2008

Files in This Item:
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AL564246.pdf532.03 kBAdobe PDF
Title: Passive photometric stereo from motion
Authors: Lim, Jongwoo;Ho, Jeffrey;Yang, Ming Hsuan;Kriegman, David
subject: Science & Technology
Year: 2005
Abstract: We introduce an iterative algorithm for shape reconstruction from multiple images of a moving (Lambertian) object illuminated by distant (and possibly time varying) lighting. Starting with an initial piecewise linear surface, the algorithm iteratively estimates a new surface based on the previous surface estimate and the photometric information available from the input image sequence. During each iteration, standard photometric stereo techniques are applied to estimate the surface normals up to an unknown generalized bas-relief transform, and a new surface is computed by integrating the estimated normals. The algorithm essentially consists of a sequence of matrix factorizations (of intensity values) followed by minimization using gradient descent (integration of the normals). Conceptually, the algorithm admits a clear geometric interpretation, which is used to provide a qualitative analysis of the algorithm's convergence. Implementation-wise, it is straightforward being based on several established photometric stereo and structure from motion algorithms. We demonstrate experimentally the effectiveness of our algorithm using several videos of hand-held objects moving in front of a fixed light and camera
Description: 

URI: http://localhost/handle/Hannan/345996
http://localhost/handle/Hannan/412778
Appears in Collections:2002-2008

Files in This Item:
File SizeFormat 
AL564246.pdf532.03 kBAdobe PDF
Title: Passive photometric stereo from motion
Authors: Lim, Jongwoo;Ho, Jeffrey;Yang, Ming Hsuan;Kriegman, David
subject: Science & Technology
Year: 2005
Abstract: We introduce an iterative algorithm for shape reconstruction from multiple images of a moving (Lambertian) object illuminated by distant (and possibly time varying) lighting. Starting with an initial piecewise linear surface, the algorithm iteratively estimates a new surface based on the previous surface estimate and the photometric information available from the input image sequence. During each iteration, standard photometric stereo techniques are applied to estimate the surface normals up to an unknown generalized bas-relief transform, and a new surface is computed by integrating the estimated normals. The algorithm essentially consists of a sequence of matrix factorizations (of intensity values) followed by minimization using gradient descent (integration of the normals). Conceptually, the algorithm admits a clear geometric interpretation, which is used to provide a qualitative analysis of the algorithm's convergence. Implementation-wise, it is straightforward being based on several established photometric stereo and structure from motion algorithms. We demonstrate experimentally the effectiveness of our algorithm using several videos of hand-held objects moving in front of a fixed light and camera
Description: 

URI: http://localhost/handle/Hannan/345996
http://localhost/handle/Hannan/412778
Appears in Collections:2002-2008

Files in This Item:
File SizeFormat 
AL564246.pdf532.03 kBAdobe PDF