Prediction of human looking behavior using interest-based image representations
學年 112
學期 1
出版（發表）日期 2023-10-12
作品名稱 Prediction of human looking behavior using interest-based image representations
作品名稱（其他語言）
著者 Guo, Jong-shenq
單位
出版者
著錄名稱、卷期、頁數 Communications in Information and Systems 23,　p.245-262
摘要 Looking behavior allows human to understand and interact with an enormous amount of information, a capacity challenging to replicate in AI systems. One of the core elements of this work is an effort to predict scan-paths from a combination of image information and past looking behavior. The success of this scan-path predication relies heavily on whether this image information can provide a sufficiently rich representation for prediction. In this paper, we show that changing representations dramatically simplifies and improves predictions of looking behavior. We introduce a representation of looking behavior that centers around interest-regions in images, defined by natural and collective looking behavior. These regions (called interest-based regions) can be used to partition images for semantic labeling and to provide a basis for shared representation across observers. Without any additional label or image information, we achieve highly accurate sequence prediction using this interest-based image representation.
關鍵字
語言 en_US
ISSN 2163-4548
期刊性質 國外
收錄於 ESCI Scopus
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
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