TY - GEN
T1 - Color-based hybrid reconstruction for endoscopy
AU - Tokgozoglu, Haluk N.
AU - Meisner, Eric M.
AU - Kazhdan, Michael
AU - Hager, Gregory D.
PY - 2012/8/20
Y1 - 2012/8/20
N2 - Three-dimensional (3D) reconstruction of images acquired during endoscopy presents an enormous opportunity for computer vision, however reconstructing geometry from such images is challenging due to lack of features. Shape From Shading (SFS) is an approach to obtain the shape of an object from a single image, but most current methods that are applicable to endoscopy are susceptible to errors caused by surfaces with differing reflectance characteristics. Another weakness of SFS is that while it has high frequency detail information, its shape is inaccurate in the low frequency sense, which makes it difficult to compare to ground truth. Multiview reconstruction (MR), on the other hand, yields reliable shape but lacks details. In this paper, we propose a novel method to perform SFS using a color projection that minimizes intensity variance caused by differing surface characteristics. We then combine the resulting reconstruction with a multiview reconstruction obtained from bundle adjustment, and combine the two reconstructions using an approach inspired by Laplacian surface editing to get a reconstruction that is accurate both in details and overall shape. We compare our results to ground truth to show improvement over existing approaches.
AB - Three-dimensional (3D) reconstruction of images acquired during endoscopy presents an enormous opportunity for computer vision, however reconstructing geometry from such images is challenging due to lack of features. Shape From Shading (SFS) is an approach to obtain the shape of an object from a single image, but most current methods that are applicable to endoscopy are susceptible to errors caused by surfaces with differing reflectance characteristics. Another weakness of SFS is that while it has high frequency detail information, its shape is inaccurate in the low frequency sense, which makes it difficult to compare to ground truth. Multiview reconstruction (MR), on the other hand, yields reliable shape but lacks details. In this paper, we propose a novel method to perform SFS using a color projection that minimizes intensity variance caused by differing surface characteristics. We then combine the resulting reconstruction with a multiview reconstruction obtained from bundle adjustment, and combine the two reconstructions using an approach inspired by Laplacian surface editing to get a reconstruction that is accurate both in details and overall shape. We compare our results to ground truth to show improvement over existing approaches.
UR - http://www.scopus.com/inward/record.url?scp=84864965574&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864965574&partnerID=8YFLogxK
U2 - 10.1109/CVPRW.2012.6239241
DO - 10.1109/CVPRW.2012.6239241
M3 - Conference contribution
AN - SCOPUS:84864965574
SN - 9781467316118
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 8
EP - 15
BT - 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012
T2 - 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012
Y2 - 16 June 2012 through 21 June 2012
ER -