Paper
17 March 2015 Visual saliency in MPEG-4 AVC video stream
Author Affiliations +
Proceedings Volume 9394, Human Vision and Electronic Imaging XX; 93940X (2015) https://doi.org/10.1117/12.2079407
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Visual saliency maps already proved their efficiency in a large variety of image/video communication application fields, covering from selective compression and channel coding to watermarking. Such saliency maps are generally based on different visual characteristics (like color, intensity, orientation, motion,…) computed from the pixel representation of the visual content. This paper resumes and extends our previous work devoted to the definition of a saliency map solely extracted from the MPEG-4 AVC stream syntax elements. The MPEG-4 AVC saliency map thus defined is a fusion of static and dynamic map. The static saliency map is in its turn a combination of intensity, color and orientation features maps. Despite the particular way in which all these elementary maps are computed, the fusion techniques allowing their combination plays a critical role in the final result and makes the object of the proposed study. A total of 48 fusion formulas (6 for combining static features and, for each of them, 8 to combine static to dynamic features) are investigated. The performances of the obtained maps are evaluated on a public database organized at IRCCyN, by computing two objective metrics: the Kullback-Leibler divergence and the area under curve.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Ammar, M. Mitrea, M. Hasnaoui, and P. Le Callet "Visual saliency in MPEG-4 AVC video stream", Proc. SPIE 9394, Human Vision and Electronic Imaging XX, 93940X (17 March 2015); https://doi.org/10.1117/12.2079407
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Visualization

Image compression

Motion models

Binary data

Databases

Feature extraction

Back to Top