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Author:

Li, Jian (Li, Jian.) | Su, Li (Su, Li.) | Wu, Bo (Wu, Bo.) | Pang, Junbiao (Pang, Junbiao.) (Scholars:庞俊彪) | Wang, Chunfeng (Wang, Chunfeng.) | Wu, Zhe (Wu, Zhe.) | Huang, Qingming (Huang, Qingming.) (Scholars:黄庆明)

Indexed by:

CPCI-S

Abstract:

We proposed a novel model to predict human's visual attention when free-viewing webpages. Compared with natural images, webpages are usually full of salient regions such as logos, text, and faces, while few of them attract human's attention in a short sight. Moreover, webpages perform distinct viewing patterns which are quite different from the natural images In this paper, we introduced multi-features according to our observation on webpages characters and related eye-tracking data. Further, in order to achieve a flexible adaptation to various types of webpages, we employed a machine-learning framework based on our proposed features. Experimental results demonstrate that our model outperforms other state-of-the-art methods in webpage saliency prediction.

Keyword:

Webpages viewing Support vector machine Multi-features Saliency

Author Community:

  • [ 1 ] [Li, Jian]Beijing Univ Posts & Telecommun, Beijing, Peoples R China
  • [ 2 ] [Su, Li]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China
  • [ 3 ] [Wang, Chunfeng]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China
  • [ 4 ] [Wu, Zhe]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China
  • [ 5 ] [Huang, Qingming]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China
  • [ 6 ] [Su, Li]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China
  • [ 7 ] [Wang, Chunfeng]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China
  • [ 8 ] [Wu, Zhe]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China
  • [ 9 ] [Huang, Qingming]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China
  • [ 10 ] [Wu, Bo]Capital Med Univ, Beijing, Peoples R China
  • [ 11 ] [Pang, Junbiao]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing, Peoples R China

Reprint Author's Address:

  • 黄庆明

    [Su, Li]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China;;[Huang, Qingming]Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Mgmt, Beijing, Peoples R China;;[Su, Li]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China;;[Huang, Qingming]Chinese Acad Sci, Inst Comp Teth, Key Lab Intel Inf Proc, Beijing 100864, Peoples R China

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Source :

2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)

ISSN: 1522-4880

Year: 2016

Page: 674-678

Language: English

Cited Count:

WoS CC Cited Count: 23

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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