Volumetric stereo with silhouette and feature constraints
Author(s) -
J. Starck,
Adrian Hilton,
Gregor Miller
Publication year - 2006
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.20.121
Subject(s) - silhouette , artificial intelligence , computer vision , feature (linguistics) , computer science , consistency (knowledge bases) , enhanced data rates for gsm evolution , surface (topology) , surface reconstruction , pattern recognition (psychology) , mathematics , geometry , philosophy , linguistics
This paper presents a novel volumetric reconstruction technique that combines shape-from-silhouette with stereo photo-consistency in a global optimisation that enforces feature constraints across multiple views. Human shape reconstruction is considered where extended regions of uniform appearance, complex self-occlusions and sparse feature cues represent a challenging problem for conventional reconstruction techniques. A unified approach is introduced to first reconstruct the occluding contours and left-right consistent edge contours in a scene and then incorporate these contour constraints in a global surface optimisation using graph-cuts. The proposed technique maximises photo-consistency on the surface, while satisfying silhouette constraints to provide shape in the presence of uniform surface appearance and edge feature constraints to align key image features across views.
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