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Multispectral object segmentation and retrieval in surveillance video
Ó Conaire, Ciarán; O'Connor, Noel E.; Cooke, Eddie; Smeaton, Alan F.
This paper describes a system for object segmentation and feature extraction for surveillance video. Segmentation is performed by a dynamic vision system that fuses information from thermal infrared video with standard CCTV video in order to detect and track objects. Separate background modelling in each modality and dynamic mutual information based thresholding are used to provide initial foreground candidates for tracking. The belief in the validity of these candidates is ascertained using knowledge of foreground pixels and temporal linking of candidates. The transferable belief model is used to combine these sources of information and segment objects. Extracted objects are subsequently tracked using adaptive thermo-visual appearance models. In order to facilitate search and classification of objects in large archives, retrieval features from both modalities are extracted for tracked objects. Overall system performance is demonstrated in a simple retrieval scenario
Keyword(s): Digital video; Information retrieval; Infrared image sensors; Infrared surveillance; Tracking; Video signal processing
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Ó Conaire, Ciarán, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <>, Cooke, Eddie and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <> (2006) Multispectral object segmentation and retrieval in surveillance video. In: ICIP 2006 - 13th International Conference on Image Processing, 8-11 October 2006, Atlanta, Georgia.
Publisher(s): Institute of Electrical and Electronics Engineers
File Format(s): application/pdf
Related Link(s):,
First Indexed: 2009-11-05 02:00:25 Last Updated: 2019-02-09 07:05:02