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Modeling 3D objects from range maps and color images using a warping-based approach

Summary: Modeling 3D objects from range maps and color images using a
warping-based approach
Faysal Boughorbel*
, Andreas Koschan, and Mongi Abidi
Imaging, Robotics and Intelligent Systems Lab, Department of Electrical and Computer
Engineering, 409 Ferris Hall, The University of Tennessee, Knoxville, TN, 37996, United States
In this paper we describe a new method for the modeling of objects with known generic shape such as human faces from
video and range data. The method combines the strengths of active laser scanning and passive Shape from Motion
techniques. Our approach consists of first reconstructing a few feature-points that can be reliably tracked throughout a
video sequence of the object. These features are mapped to corresponding 3D points in a generic 3D model reconstructed
from dense and accurate range data acquired only once. The resulting 3D-3D set of matches is used to warp the generic
model into the actual object visible in the video stream using thin-plate splines interpolation. Our method avoids the
problems of dense matching encountered in stereo algorithms. Furthermore, in the case of face reconstruction, this
method provides dense models while not requiring the invasive laser scanning of faces.
Keywords: 3D modeling, warping, shape from motion, range, video, face reconstruction
Two important means of acquiring 3D models of real world scenes and objects are range scanners and stereovision
systems. The first approach is usually implemented through laser-range mapping techniques, which result in dense depth
maps, with relatively high accuracy. On the other hand, stereo methods reconstruct the scene geometry by finding


Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee


Collections: Computer Technologies and Information Sciences