Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-23
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis.
Firstly, this algorithm employs motion vector (MV) to extract temporal saliency region through fast MV noise filtering and translational MV checking procedure.
Secondly, spatial saliency region is detected based on optimal prediction mode distributions in I-frame and P-frame.
Then, it combines the spatiotemporal saliency detection results to define the video region of interest (VROI).
The simulation results validate that the proposed algorithm can avoid a large amount of computation work in the visual perception characteristics analysis processing compared with other existing algorithms; it also has better performance in saliency detection for videos and can realize fast saliency detection.
It can be used as a part of the video standard codec at medium-to-low bit-rates or combined with other algorithms in fast video coding.
American Psychological Association (APA)
Liu, Pengyu& Jia, Kebin. 2013. Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-1032758
Modern Language Association (MLA)
Liu, Pengyu& Jia, Kebin. Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding. The Scientific World Journal No. 2013 (2013), pp.1-15.
https://search.emarefa.net/detail/BIM-1032758
American Medical Association (AMA)
Liu, Pengyu& Jia, Kebin. Low-Complexity Saliency Detection Algorithm for Fast Perceptual Video Coding. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-1032758
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032758