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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Can Saliency Map Models Predict Human Egocentric Visual Attention?
verfasst von : Kentaro Yamada, Yusuke Sugano, Takahiro Okabe, Yoichi Sato, Akihiro Sugimoto, Kazuo Hiraki
Erschienen in: Computer Vision – ACCV 2010 Workshops
Verlag: Springer Berlin Heidelberg
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The validity of using conventional saliency map models to predict human attention was investigated for video captured with an egocentric camera. Since conventional visual saliency models do not take into account visual motion caused by camera motion, high visual saliency may be erroneously assigned to regions that are not actually visually salient. To evaluate the validity of using saliency map models for egocentric vision, an experiment was carried out to examine the correlation between visual saliency maps and measured gaze points for egocentric vision. The results show that conventional saliency map models can predict visually salient regions better than chance for egocentric vision and that the accuracy decreases significantly with an increase in visual motion induced by egomotion, which is presumably compensated for in the human visual system. This latter finding indicates that a visual saliency model is needed that can better predict human visual attention from egocentric videos.