Authors:
Ferran Diego
1
;
Georgios Evangelidis
2
and
Joan Serrat
3
Affiliations:
1
Universitat Autonoma de Barcelona and University of Heidelberg, Spain
;
2
University of Patras, Greece
;
3
Universitat Autonoma de Barcelona, Spain
Keyword(s):
Video surveillance,Video synchronization, Video alignment, Change detection.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Data Engineering
;
Human-Computer Interaction
;
Image and Video Analysis
;
Information Retrieval
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Physiological Computing Systems
;
Software Engineering
;
Video Analysis
Abstract:
This paper addresses the problem of video surveillance by mobile cameras. We present a method that allows
online change detection in night–time outdoor surveillance. Because of the camera movement, background
frames are not available and must be ”localized“ in former sequences and registered with the current frames.
To this end, we propose a Frame Localization And Registration (FLAR) approach that solves the problem
efficiently. Frames of former sequences define a database which is queried by current frames in turn. To
quickly retrieve nearest neighbors, database is indexed through a visual dictionary method based on the SURF
descriptor. Furthermore, the frame localization is benefited by a temporal filter that exploits the temporal
coherence of videos. Next, the recently proposed ECC alignment scheme is used to spatially register the
synchronized frames. Finally, change detection methods apply to aligned frames in order to mark suspicious
areas. Experiments with real night sequences
recorded by in-vehicle cameras demonstrate the performance of
the proposed method and verify its efficiency and effectiveness against other methods.
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