Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 232585.0, MPI für biologische Kybernetik / Biologische Kybernetik
Learning Depth From Stereo
Authors:Sinz, F.; Quiñonero-Candela, J.; Bakir, G.H.; Rasmussen, C.E.; Franz, M.O.
Editors:Rasmussen, C. E.; Buelthoff, H. H.; Giese, M. A.; Schoelkopf, B.
Date of Publication (YYYY-MM-DD):2004
Title of Proceedings:Pattern Recognition, Proc. 26th DAGM Symposium
Start Page:245
End Page:252
Physical Description:8
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:We compare two approaches to the problem of estimating the depth
of a point in space from observing its image position in two
different cameras: 1.~The classical photogrammetric approach
explicitly models the two cameras and estimates their intrinsic
and extrinsic parameters using a tedious calibration procedure;
2.~A generic machine learning approach where the mapping from
image to spatial coordinates is directly approximated by a Gaussian Process regression. Our results show that the generic
learning approach, in addition to simplifying the procedure of
calibration, can lead to higher depth accuracies than classical
calibration although no specific domain knowledge is used.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:2644
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.