• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

Lin, Y. (Lin, Y..) [1] | Yu, Y. (Yu, Y..) [2]

Indexed by:

Scopus

Abstract:

Detecting region of bottom-up visual attention in videos has become increasingly popular due to its wide applicability. In the meantime, it is a challenging problem that saliency only stimulated by low-level features and without any prior knowledge. In this paper, we propose a pure bottom-up method to compute video attention which is easy to implement. It involves three parts: Low-level feature extraction, saliency calculation and maps combination. The saliency of visual attention is calculated by using Locality-constrained Linear Coding in multiple temporal scales. Experimental results demonstrate that the proposed method can successfully detect the most salient regions which human eye will typically focus on. © 2017 IEEE.

Keyword:

Community:

  • [ 1 ] [Lin, Y.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China
  • [ 2 ] [Yu, Y.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China

Reprint 's Address:

Email:

Show more details

Related Keywords:

Related Article:

Source :

2017 4th International Conference on Systems and Informatics, ICSAI 2017

Year: 2017

Volume: 2018-January

Page: 1324-1329

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

Affiliated Colleges:

Online/Total:189/10048651
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1