Paper Info
Title
Line Cue Augmented Perspective Structure From Motion
Abstract
Object shape and camera motion can be recovered from a sequence of images using a set of feature point correspondences. This is known as the structure from notion problem and the factorization method is the most widely applied solution due to its stability and robustness. This paper describes a method of employing geometrical features available in a scene, in the form of straight lines, in a factorization-based structure from motion application. The effects of inaccuracies of feature data can be reduced by constraining the reconstructed features corresponding to the points forming straight lines. Our main contribution in this paper is the use of such geometric features to refine the shape recovery using the current advancements in the factorization method. Reconstructed features are mapped to straight lines and the measurement matrix containing image feature data is updated with the adjusted data. This increases the accuracy of reconstruction perceptually as well as quantitatively. The algorithm consists of first obtaining the reconstruction using singular value decomposition. Mapping 3D lines to sets of feature points is then carried out. The measurement matrix is refined followed by a second phase of factorization and normalization to obtain metric reconstruction. Results pertaining to both synthetic and actual sequences of images are presented.
Year
DOI
Venue
2006
10.1117/12.594614
IMAGE PROCESSING: ALGORITHMS AND SYSTEMS IV
Keywords
Field
DocType
structure from motion, perspective reconstruction, 3D line mapping
Iterative reconstruction,Structure from motion,Computer vision,Singular value decomposition,Normalization (statistics),Image processing,Artificial intelligence,Factorization,Motion estimation,Mathematics,Feature data
Conference
Volume
ISSN
Citations 
5672
0277-786X
0
PageRank 
References 
Authors
0.34
1
2
Name
Order
Citations
PageRank
Jagath Samarabandu113320.50
Ranga Rodrigo2468.96