Low-complexity camera ego-motion estimation algorithm for real time applications

Publikationstyp
Conference Paper
Date Issued
2004
Sprache
English
Author(s)
Shafait, Faisal  
Grimm, Marco  
Grigat, Rolf-Rainer  
Institut
Bildverarbeitungssysteme E-2  
TORE-URI
http://hdl.handle.net/11420/10079
Start Page
131
End Page
136
Article Number
1492859
Citation
Proceedings of INMIC 2004 - 8th International Multitopic Conference: 1492859, 131-136 (2004)
Contribution to Conference
8th International Multitopic Conference (INMIC 2004)  
Publisher DOI
10.1109/INMIC.2004.1492859
Scopus ID
2-s2.0-33845367784
Publisher
National University of Computer and Emerging Sciences [u.a.]
This contribution presents a low-complexity camera egomotion estimation algorithm for real-time applications. The algorithm uses a feature based approach for motion estimation. A new method is introduced for feature selection which limits the number of feature points to be tracked and has a low dependency on structure in the image. Both these factors are important in real time applications, as lesser features to track result in lower computational complexity and lesser dependency on image structure results in smaller variations in computational time for different images. This gain in speed is achieved at the cost of a slightly reduced robustness and accuracy. This trade-off between speed and accuracy pays off particularly in static scenes where high reduction in computational cost is achieved without the accuracy penalty. This algorithm can be used in applications where an estimate of camera motion is required and low computational complexity is of primary concern.
DDC Class
600: Technik