Issue No. 10 - October (2011 vol. 33)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2011.37
Gabriel J. Brostow , University College London, London
Carlos Hernández , Google Inc.
George Vogiatzis , Aston University, Birmingham
Björn Stenger , Toshiba Research Europe Ltd., Cambridge
Roberto Cipolla , University of Cambridge, Cambridge
We present an algorithm and the associated single-view capture methodology to acquire the detailed 3D shape, bends, and wrinkles of deforming surfaces. Moving 3D data has been difficult to obtain by methods that rely on known surface features, structured light, or silhouettes. Multispectral photometric stereo is an attractive alternative because it can recover a dense normal field from an untextured surface. We show how to capture such data, which in turn allows us to demonstrate the strengths and limitations of our simple frame-to-frame registration over time. Experiments were performed on monocular video sequences of untextured cloth and faces with and without white makeup. Subjects were filmed under spatially separated red, green, and blue lights. Our first finding is that the color photometric stereo setup is able to produce smoothly varying per-frame reconstructions with high detail. Second, when these 3D reconstructions are augmented with 2D tracking results, one can register both the surfaces and relax the homogenous-color restriction of the single-hue subject. Quantitative and qualitative experiments explore both the practicality and limitations of this simple multispectral capture system.
Photometric stereo, multispectral, single view, video normals.
G. J. Brostow, B. Stenger, G. Vogiatzis, C. Hernández and R. Cipolla, "Video Normals from Colored Lights," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 33, no. , pp. 2104-2114, 2011.