Benedek, Csaba (2013) A Two-Layer Marked Point Process Framework for Multilevel Object Population Analysis. In: International Conference on Image Analysis and Recognition, June 26-28, 2013, Póvoa de Varzim, Portugal. (In Press)

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Abstract

In this paper we introduce a probabilistic approach for extracting object ensembles from various digital images used by machine vision applications. The proposed framework extends conventional Marked Point Process models by allowing corresponding entities to form coherent object groups, by a Bayesian segmentation of the population. A global optimization process attempts to find the optimal configuration of entities and entity groups, considering the observed data, prior knowledge, and local interactions between the neighboring and semantically related objects. The proposed method is demonstrated in three different application areas: built in area analysis in remotely sensed images, traffic monitoring on airborne Lidar data and optical inspection of printed circuit boards.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	to appear in Lecture Notes in Computer Science
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Distributed Events Analysis Research Laboratory
Depositing User:	Csaba Benedek
Date Deposited:	13 Mar 2013 09:22
Last Modified:	17 Dec 2013 07:57
URI:	https://eprints.sztaki.hu/id/eprint/7149

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• A Two-Layer Marked Point Process Framework for Multilevel Object Population Analysis. (deposited 13 Mar 2013 09:22) [Currently Displayed]
  • A Two-Layer Marked Point Process Framework for Multilevel Object Population Analysis. (deposited 14 Mar 2013 11:18)

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