DocumentCode :
3056551
Title :
Local dependency analysis in probabilistic scene estimation
Author :
Grundmann, Thilo ; Eidenberger, Robert ; Zollner, Raoul D.
Author_Institution :
Inf. & Commun., Siemens Corp. Technol., Munich
fYear :
2008
fDate :
27-29 May 2008
Firstpage :
1
Lastpage :
6
Abstract :
A general solution to the problem of jointly estimating the state of multiple entities is regarded computationally challenging at the time. Most solutions are based on the application of wide assumptions of independence. In many situations and constellations of entities, this is sufficient and leads to high quality results. In some situations as occlusion for instance the assumption of independence is violated heavily resulting in considerable errors. The proposed approach considers local dependencies, allowing to increase the accuracy of the estimation punctually, depending on application requirements, such as high precision localization for grasping operations or rough precision for semantic localization.
Keywords :
computer vision; object detection; application requirements; local dependencies; local dependency analysis; probabilistic scene estimation; rough precision; semantic localization; Bayesian methods; Communications technology; Filters; Information analysis; Layout; Mechatronics; Mobile robots; State estimation; State-space methods; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Its Applications, 2008. ISMA 2008. 5th International Symposium on
Conference_Location :
Amman
Print_ISBN :
978-1-4244-2033-9
Electronic_ISBN :
978-1-4244-2034-6
Type :
conf
DOI :
10.1109/ISMA.2008.4648815
Filename :
4648815
Link To Document :
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