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Proceedings Paper

Saliency detection for videos using 3D FFT local spectra
Author(s): Zhiling Long; Ghassan AlRegib
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Paper Abstract

Bottom-up spatio-temporal saliency detection identifies perceptually important regions of interest in video sequences. The center-surround model proves to be useful for visual saliency detection. In this work, we explore using 3D FFT local spectra as features for saliency detection within the center-surround framework. We develop a spectral location based decomposition scheme to divide a 3D FFT cube into two components, one related to temporal changes and the other related to spatial changes. Temporal saliency and spatial saliency are detected separately using features derived from each spectral component through a simple center-surround comparison method. The two detection results are then combined to yield a saliency map. We apply the same detection algorithm to different color channels (YIQ) and incorporate the results into the final saliency determination. The proposed technique is tested with the public CRCNS database. Both visual and numerical evaluations verify the promising performance of our technique.

Paper Details

Date Published: 17 March 2015
PDF: 6 pages
Proc. SPIE 9394, Human Vision and Electronic Imaging XX, 93941G (17 March 2015); doi: 10.1117/12.2077762
Show Author Affiliations
Zhiling Long, Georgia Institute of Technology (United States)
Ghassan AlRegib, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 9394:
Human Vision and Electronic Imaging XX
Bernice E. Rogowitz; Thrasyvoulos N. Pappas; Huib de Ridder, Editor(s)

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