Saliency Priority of Individual Bottom-Up Attributes in Designing Visual Attention Models

Jila Hosseinkhani, C. Joslin
{"title":"Saliency Priority of Individual Bottom-Up Attributes in Designing Visual Attention Models","authors":"Jila Hosseinkhani, C. Joslin","doi":"10.4018/IJSSCI.2018100101","DOIUrl":null,"url":null,"abstract":"A key factor in designing saliency detection algorithms for videos is to understand how different visual cues affect the human perceptual and visual system. To this end, this article investigated the bottom-up features including color, texture, and motion in video sequences for a one-by-one scenario to provide a ranking system stating the most dominant circumstances for each feature. In this work, it is considered the individual features and various visual saliency attributes investigated under conditions in which the authors had no cognitive bias. Human cognition refers to a systematic pattern of perceptual and rational judgments and decision-making actions. First, this paper modeled the test data as 2D videos in a virtual environment to avoid any cognitive bias. Then, this paper performed an experiment using human subjects to determine which colors, textures, motion directions, and motion speeds attract human attention more. The proposed benchmark ranking system of salient visual attention stimuli was achieved using an eye tracking procedure.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Softw. Sci. Comput. Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJSSCI.2018100101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

A key factor in designing saliency detection algorithms for videos is to understand how different visual cues affect the human perceptual and visual system. To this end, this article investigated the bottom-up features including color, texture, and motion in video sequences for a one-by-one scenario to provide a ranking system stating the most dominant circumstances for each feature. In this work, it is considered the individual features and various visual saliency attributes investigated under conditions in which the authors had no cognitive bias. Human cognition refers to a systematic pattern of perceptual and rational judgments and decision-making actions. First, this paper modeled the test data as 2D videos in a virtual environment to avoid any cognitive bias. Then, this paper performed an experiment using human subjects to determine which colors, textures, motion directions, and motion speeds attract human attention more. The proposed benchmark ranking system of salient visual attention stimuli was achieved using an eye tracking procedure.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
视觉注意模型设计中个体自底向上属性的显著性优先级
设计视频显著性检测算法的一个关键因素是了解不同的视觉线索如何影响人类的感知和视觉系统。为此,本文研究了自底向上的特征,包括视频序列中的颜色、纹理和运动,以提供一个排名系统,说明每个特征的最主要情况。在这项工作中,它被认为是在作者没有认知偏见的条件下调查的个体特征和各种视觉显著性属性。人的认知是一种感性的、理性的判断和决策行为的系统模式。首先,本文将测试数据建模为虚拟环境中的二维视频,以避免任何认知偏差。然后,通过人体实验来确定哪些颜色、纹理、运动方向和运动速度更能吸引人的注意力。采用眼动追踪方法实现了显著性视觉注意刺激的基准排序系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Knowledge Discovery of Hospital Medical Technology Based on Partial Ordered Structure Diagrams Artificial Intelligence Techniques to improve cognitive traits of Down Syndrome Individuals: An Analysis TA-WHI: Text Analysis of Web-Based Health Information Detection of Distributed Denial of Service (DDoS) Attacks Using Computational Intelligence and Majority Vote-Based Ensemble Approach Model-Based Method for Optimisation of an Adaptive System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1