NDLI: Attention computation model for coal-mine surveillance video based on non-uniform sampling in spatial domain and time domain

Content Provider	IEEE Xplore Digital Library
Author	Gang Hua Lei Zhou Zhao Xu Dongmei Xu
Copyright Year	2010
Description	Author affiliation: School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China (Gang Hua; Lei Zhou; Zhao Xu; Dongmei Xu)
Abstract	There are few methods to deal with the coal-mine surveillance video, the only few existing methods all make use of the traditional image engineering ideas. Visual attention has the prominent functions that can reduce computation and accelerate the computing speed. This paper firstly analyzes the limitations of existing down-top attention model in the application of coalmine surveillance video, then proposes a new visual attention computation model based on sequential scale space and multi-features. Different from the existing model, non-uniform sampling in spatial domain of our algorithm is expressed as discrete structure of sequential scale space, and we choose the modified Bessel function as the smooth kernel, in time domain, we establish a threshold for frame sampling. About feature extraction, we choose the motion conspicuity, wavelet package decomposition and gray intensity as measures of saliency, DOG (Difference of Gaussian) operator as the generalized method. Finally, a global saliency map for the interesting objects is formed. The experiment results show the flexibility and effectiveness of this model.
Starting Page	107
Ending Page	110
File Size	385411
Page Count	4
File Format	PDF
ISBN	9781424467358
e-ISBN	9781424467372
e-ISBN	9781424467365
DOI	10.1109/PRIMEASIA.2010.5604951
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Computational modeling Surveillance Hidden Markov models Time domain analysis Feature extraction Kernel
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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