Semiautomatic Visual-Attention Modeling and Its Application to Video Compression

Авторы: Gitman Yury, Erofeev Mikhail, Vatolin Dmitriy, Bolshakov Andrey, Fedorov Alexey
Сборник: 2014 IEEE International Conference on Image Processing (ICIP) (ICIP 2014)
Год издания: 2014
Место издания: Paris, France
Первая страница: 1105
Последняя страница: 1109
DOI: 10.1109/ICIP.2014.7025220
Аннотация: This research aims to sufficiently increase the quality of visual-attention modeling to enable practical applications. We found that automatic models are significantly worse at predicting attention than even single-observer eye tracking. We propose a semiautomatic approach that requires eye tracking of only one observer and is based on time consistency of the observer’s attention. Our comparisons showed the high objective quality of our proposed approach relative to automatic methods and to the results of single-observer eye tracking with no postprocessing. We demonstrated the practical applicability of our proposed concept to the task of saliency-based video compression.
Добавил в систему: Ерофеев Михаил Викторович

№	Имя	Описание	Имя файла	Размер	Добавлен
1.	Полный текст		2014_Semiautomatic_visual-attention_modeling_and_its_applic…	6,0 МБ	18 мая 2016 [dmitriyv]

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