.png){kind=icon}
返回
Human Visual System-Based Saliency Detection for High Dynamic Range Content
.png){kind=icon}
PRE
AI
DOI：10.1109/TMM.2016.2522639.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The human visual system (HVS) attempts to select salient areas to reduce cognitive processing efforts. Computational models of visual attention try to predict the most relevant and important areas of videos or images viewed by the human eye. Such models, in turn, can be applied to areas such as computer graphics, video coding, and quality assessment. Although several models have been proposed, only one of them is applicable to high dynamic range (HDR) image content, and no work has been done for HDR videos. Moreover, the main shortcoming of the existing models is that they cannot simulate the characteristics of HVS under the wide luminous range found in HDR content. This paper addresses these issues by presenting a computational approach to model the bottom-up visual saliency for HDR input by combining spatial and temporal visual features. An analysis of eye movement data affirms the effectiveness of the proposed model. Comparisons employing three well-known quantitative metrics show that the proposed model substantially improves predictions of visual attention for HDR content.
Keyword:
Eye tracking
high dynamic range (HDR)
saliency map
visual attention
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
4.5K
被引数:
2.4W
机构
引用论文
.png){kind=icon}
Preliminary Study of Heavy Metal (Zn, Pb, Cr, Ni) Contaminations in Langat River Estuary, Selangor
OAAI
OAAI分享收藏分享收藏
查看更多内容