NDLI: Video attention saliency mapping using pulse coupled neural network and optical flow

Content Provider	IEEE Xplore Digital Library
Author	Qiling Ni Xiaodong Gu
Copyright Year	2014
Description	Author affiliation: Dept. of Electron. Eng., Fudan Univ., Shanghai, China (Qiling Ni; Xiaodong Gu)
Abstract	This paper proposes a biologically inspired video attention saliency detector by combining optical flow and topological properties. In this paper, we expound how to utilize feature informations of video and how to use topological property and optical flow based on attention detection for target tracking. Visual attention used in our model is a consequence of tuning of some saliency features such as color, shape and motion. The model (OFTPA-Optical Flow Topological Properties Attention) we proposed for motion attention saliency detection includes two stages. First stage focuses on extracting saliency features, including optical-flow velocity field, topological properties and Intensity, from video. The second integrates the traditional saliency features and an extra position prediction calculated from optical-flow field, to form bottom-up saliency maps which indicate where the object candidates are located. Spatiotemporal saliency maps are obtained from the phase spectrum of a video's hypercomplex Fourier transform. Experimental results show that the OFTPA model takes advantage over other models such as PQFT in complex background.
Starting Page	340
Ending Page	344
File Size	3117925
Page Count	5
File Format	PDF
ISSN	21614407
e-ISBN	9781479914845
DOI	10.1109/IJCNN.2014.6889424
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Image motion analysis Optical imaging Optical reflection Quaternions Biomedical optical imaging Adaptive optics attention saliency map optical flow topological property Unit-linking PCNN video
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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