This paper presents a novel Photometric Stereo approach for static views that recasts the problem into a piecewise formulation. The proposed algorithm, called Piecewise Photometric Stereo (PPS), entails several advantages in respect to previous global approaches. It is intrinsically more efficient, since reconstructing the surface in patches is computationally faster than reconstructing the global surface. Each patch has been associated an individual photometric model rather than a single global model as used in classical approaches. In this way, the piecewise formulation may grasp more complex lighting effects. Finally, the global metric properties of the shape is preserved using the multi-view constraints. In this pipeline, structure from motion is exploited to define such set of constraints and to compose a 3D mesh representing the metric structure of the object. Real results with ground truth show the positive performance of our algorithm compared with a classical global approach for Photometric Stereo.

Piecewise single view Photometric Stereo with multi-view constraints

MURINO, Vittorio
2012-01-01

Abstract

This paper presents a novel Photometric Stereo approach for static views that recasts the problem into a piecewise formulation. The proposed algorithm, called Piecewise Photometric Stereo (PPS), entails several advantages in respect to previous global approaches. It is intrinsically more efficient, since reconstructing the surface in patches is computationally faster than reconstructing the global surface. Each patch has been associated an individual photometric model rather than a single global model as used in classical approaches. In this way, the piecewise formulation may grasp more complex lighting effects. Finally, the global metric properties of the shape is preserved using the multi-view constraints. In this pipeline, structure from motion is exploited to define such set of constraints and to compose a 3D mesh representing the metric structure of the object. Real results with ground truth show the positive performance of our algorithm compared with a classical global approach for Photometric Stereo.
2012
Surface reconstruction, Shape, Lighting, Image reconstruction, Stereo vision, Measurement, Pipelines
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/961551
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