TY - GEN
T1 - Feature-based 3D reconstruction model for close-range objects and its application to human finger
AU - Liu, Feng
AU - Shen, Linlin
AU - Zhang, David
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2015.
PY - 2015
Y1 - 2015
N2 - This paper addresses the problem of feature-based 3D reconstruction model for close-range objects. Since it is almost impossible to find pixel-to-pixel correspondences from 2D images by algorithms when the object is imaged on a close range, the selection of feature correspondences, as well as the number and distribution of them, play important roles in the reconstruction accuracy. Then, features on representative objects are analyzed and discussed. The impact of the number and distribution of feature correspondences is analyzed by reconstructing an object with standard cylinder shape by following the reconstruction model introduced in the paper. After that, three criteria are set to guide the selection of feature correspondences for more accurate 3D reconstruction. These criteria are finally applied to the human finger since it is a typical close-range object and different number and distribution of feature correspondences can be established automatically from its 2D fingerprints. The effectiveness of the setting criteria is demonstrated by comparing the accuracy of reconstructed finger shape based on different fingerprint feature correspondences with the corresponding 3D point cloud data obtained by structured light illumination (SLI) technique which is taken as a ground truth in the paper.
AB - This paper addresses the problem of feature-based 3D reconstruction model for close-range objects. Since it is almost impossible to find pixel-to-pixel correspondences from 2D images by algorithms when the object is imaged on a close range, the selection of feature correspondences, as well as the number and distribution of them, play important roles in the reconstruction accuracy. Then, features on representative objects are analyzed and discussed. The impact of the number and distribution of feature correspondences is analyzed by reconstructing an object with standard cylinder shape by following the reconstruction model introduced in the paper. After that, three criteria are set to guide the selection of feature correspondences for more accurate 3D reconstruction. These criteria are finally applied to the human finger since it is a typical close-range object and different number and distribution of feature correspondences can be established automatically from its 2D fingerprints. The effectiveness of the setting criteria is demonstrated by comparing the accuracy of reconstructed finger shape based on different fingerprint feature correspondences with the corresponding 3D point cloud data obtained by structured light illumination (SLI) technique which is taken as a ground truth in the paper.
UR - http://www.scopus.com/inward/record.url?scp=84951799359&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-48570-5_37
DO - 10.1007/978-3-662-48570-5_37
M3 - Conference contribution
AN - SCOPUS:84951799359
SN - 9783662485699
T3 - Communications in Computer and Information Science
SP - 379
EP - 393
BT - Computer Vision CCF Chinese Conference, CCCV 2015, Proceedings
A2 - Wang, Liang
A2 - Zha, Hongbin
A2 - Chen, Xilin
A2 - Miao, Qiguang
PB - Springer Verlag
T2 - 1st Chinese Conference on Computer Vision, CCCV 2015
Y2 - 18 September 2015 through 20 September 2015
ER -