Paper
17 August 1994 Line correspondence in aerial images using stochastic relaxation and minimum description length criterion
Peter Axelsson
Author Affiliations +
Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182915
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany
Abstract
The problem of line correspondence in multi images is approached using a clustering procedure in object space, thus being independent of the number of images used. Lines are located in the images and by applying object depending restrictions the main directions of the object, corresponding to the vanishing points in the images, can be found. Lines co-linear with the vanishing directions are projected on cluster planes, having the main directions as surface normals. A possible 3D line will then exist where at least two lines intersect in a cluster plane. By accumulating the cluster plane information to the cluster plane axis lines co-planar with each other will be accumulated to each other. For finding the correct maxima on the cluster axis the method of simulated annealing is applied. By using the minimum description length criterion for computing the weights, different types of information are combined in a common framework. When the (sub)optimum solution of the minimizing function is found the line correspondences are directly derived from the found maxima. Results of a building covered by four aerial images are presented.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter Axelsson "Line correspondence in aerial images using stochastic relaxation and minimum description length criterion", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182915
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

3D modeling

3D image processing

Buildings

Algorithms

Edge detection

Stochastic processes

Back to Top