NDLI: Dynamic attentive system for omnidirectional video

Content Provider	IEEE Xplore Digital Library
Author	Bogdanova, I. Bur, A. Farine, P.-A.
Copyright Year	2009
Description	Author affiliation: Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Microengineering (IMT), Pattern Recognition Laboratory (PARLAB), Rue A.-L- Breguet 2, 2000-Neuchâtel, Switzerland (Bogdanova, I.; Bur, A.; Farine, P.-A.)
Abstract	In this paper, we propose a dynamic attentive system for detecting the most salient regions of interest in omnidirectional video. The spot selection is based on computer modeling of dynamic visual attention. In order to operate on video sequences, the process encompasses the multiscale contrast detection of static and motion information, as well as fusion of the information in a scalar map called saliency map. The processing is performed in spherical geometry. While the static contribution collected in the static saliency map relies on our previous work, we propose a novel motion model based on block matching algorithm computed on the sphere. A spherical motion field pyramid is first estimated from two consecutive omnidirectional images by varying the block size. This latter constitutes the input of the motion model. Then, the motion saliency map is obtained by applying a multiscale motion contrast detection method in order to highlight the most salient motion regions. Finally, both static and motion saliency maps are integrated into a spherical dynamic saliency map. To illustrate the concept, the proposed attentive system is applied to real omnidirectional video sequences.
Starting Page	1
Ending Page	4
File Size	1773575
Page Count	4
File Format	PDF
ISBN	9781424445936
DOI	10.1109/PCS.2009.5167395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Solid modeling Computer vision Motion estimation Video sequences Laboratories Pattern recognition Application software Geometry block matching on the sphere omnidirectional image processing dynamic visual attention Feature extraction Motion detection
Content Type	Text
Resource Type	Article

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