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Visual planesbased simultaneous localization and model refinement for augmented reality

Title: Visual planesbased simultaneous localization and model refinement for augmented reality
Authors: Fabien Servant; Eric Marchand; Pascal Houlier; Isabelle Marchal
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://figment.cse.usf.edu/~sfefilat/data/papers/ThBCT9.23.pdf.
Publication Year: 2008
Collection: CiteSeerX
Description: This paper presents a method for camera pose tracking that uses a partial knowledge about the scene. The method is based on monocular vision Simultaneous Localization And Mapping (SLAM). With respect to classical SLAM implementations, this approach uses previously known information about the environment (rough map of the walls) and profits from the various available databases and blueprints to constraint the problem. This method considers that the tracked image patches belong to known planes (with some uncertainty in their localization) and that SLAM map can be represented by associations of cameras and planes. In this paper, we propose an adapted SLAM implementation and detail the considered models. We show that this method gives good results for a real sequence with complex motion for augmented reality (AR) application. 1
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.1161; http://figment.cse.usf.edu/~sfefilat/data/papers/ThBCT9.23.pdf
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.1161; http://figment.cse.usf.edu/~sfefilat/data/papers/ThBCT9.23.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.48A43C7B
Database: BASE