-
Thematic Saliency Detection Using Spatial-Temporal Context
AbstractWe propose a new measurement of video saliency termed thematic video saliency. Video saliency is detected in terms of finding the thematic objects that frequently appear at the salient positions in the video scenes. By representing all image segments in the video as the spatial-temporal context, we build an affinity graph among them, and formulate the thematic object discovery as a novel cohesive sub-graph mining problem. A trust region algorithm is also proposed to solve the challenging optimization problem. Unlike individual image saliency or co-saliency analysis, our proposed video saliency fully incorporates the whole spatialtemporal video context. Experiments on our newly developed eye tracking dataset as well as other two datasets further validate the effectiveness of our method on video saliency detection.
Related Material
[pdf][bibtex]@InProceedings{Luo_2013_ICCV_Workshops,
author = {Ye Luo and Gangqiang Zhao and Junsong Yuan},
title = {Thematic Saliency Detection Using Spatial-Temporal Context},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {June},
year = {2013}
}
These ICCV 2013 workshop papers are the Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
This material is presented to ensure timely dissemination of scholarly and technical work.
Copyright and all rights therein are retained by authors or by other copyright holders.
All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.