TY - GEN
T1 - A linear formulation of shape from specular flow
AU - Canas, Guillermo D.
AU - Vasilyev, Yuriy
AU - Adato, Yair
AU - Zickler, Todd
AU - Gortler, Steven
AU - Ben-Shahar, Ohad
PY - 2009/12/1
Y1 - 2009/12/1
N2 - When a curved mirror-like surface moves relative to its environment, it induces a motion field - or specular flow - on the image plane that observes it. This specular flow is related to the mirror's shape through a non-linear partial differential equation, and there is interest in understanding when and how this equation can be solved for surface shape. Existing analyses of this 'shape from specular flow equation' have focused on closed-form solutions, and while they have yielded insight, their critical reliance on externally-provided initial conditions and/or specific motions makes them difficult to apply in practice. This paper resolves these issues. We show that a suitable reparameterization leads to a linear formulation of the shape from specular flow equation. This formulation radically simplifies the reconstruction process and allows, for example, both motion and shape to be recovered from as few as two specular flows even when no externally-provided initial conditions are available. Our analysis moves us closer to a practical method for recovering shape from specular flow that operates under arbitrary, unknown motions in unknown illumination environments and does not require additional shape information from other sources.
AB - When a curved mirror-like surface moves relative to its environment, it induces a motion field - or specular flow - on the image plane that observes it. This specular flow is related to the mirror's shape through a non-linear partial differential equation, and there is interest in understanding when and how this equation can be solved for surface shape. Existing analyses of this 'shape from specular flow equation' have focused on closed-form solutions, and while they have yielded insight, their critical reliance on externally-provided initial conditions and/or specific motions makes them difficult to apply in practice. This paper resolves these issues. We show that a suitable reparameterization leads to a linear formulation of the shape from specular flow equation. This formulation radically simplifies the reconstruction process and allows, for example, both motion and shape to be recovered from as few as two specular flows even when no externally-provided initial conditions are available. Our analysis moves us closer to a practical method for recovering shape from specular flow that operates under arbitrary, unknown motions in unknown illumination environments and does not require additional shape information from other sources.
UR - http://www.scopus.com/inward/record.url?scp=77953218605&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2009.5459164
DO - 10.1109/ICCV.2009.5459164
M3 - Conference contribution
AN - SCOPUS:77953218605
SN - 9781424444205
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 191
EP - 198
BT - 2009 IEEE 12th International Conference on Computer Vision, ICCV 2009
T2 - 12th International Conference on Computer Vision, ICCV 2009
Y2 - 29 September 2009 through 2 October 2009
ER -