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Detection, segmentation, and tracking of moving objects in UAV videos

 
: Teutsch, Michael; Krüger, Wolfgang

:
Postprint urn:nbn:de:0011-n-2194095 (1.1 MByte PDF)
MD5 Fingerprint: 2dffd8ae2a2fad0d698512def0299ad8
© 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Erstellt am: 15.11.2012


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2012. Proceedings : 18-21 September 2012, Beijing, China
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2012
ISBN: 978-0-7695-4797-8
ISBN: 978-1-4673-2499-1 (Print)
S.313-318
International Conference on Advanced Video and Signal-Based Surveillance (AVSS) <9, 2012, Beijing>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Abstract
Automatic processing of videos coming from small UAVs offers high potential for advanced surveillance applications but is also very challenging. These challenges include camera motion, high object distance, varying object background, multiple objects near to each other, weak signalto-noise-ratio (SNR), or compression artifacts. In this paper, a video processing chain for detection, segmentation, and tracking of multiple moving objects is presented dealing with the mentioned challenges. The fundament is the detection of local image features, which are not stationary. By clustering these features and subsequent object segmentation, regions are generated representing object hypotheses. Multi-object tracking is introduced using a Kalman filter and considering the camera motion. Split or merged object regions are handled by fusion of the regions and the local features. Finally, a quantitative evaluation of object segmentation and tracking is provided.

: http://publica.fraunhofer.de/dokumente/N-219409.html