Advertisement evaluation using visual saliency based on foveated image

Authors:
Zhiguo Ma;Laiyun Qing;Jun Miao;Xilin Chen
Affiliations:
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences and Graduate School of the Chinese Academy of Sciences, Chinese Academy of Scie ...;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Venue:
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Year:
2009

Citing 2
Cited 1

Eye Fixations on Advertisements and Memory for Brands: A Model and Findings

Marketing Science
2006 Special Issue: Modeling attention to salient proto-objects

Neural Networks

Quaternion-Based spectral saliency detection for eye fixation prediction

ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a novel approach to advertisement evaluation using automatic salient regions. The salient regions are detected using a predicting model, in which the estimation are obtained by the space variant foveated image. The saliency is defined as the difference between the input image and its estimation. Then an advertisement is determined as attractive if the detected salient regions are overlapped with the interested regions of the advertisement. The experimental results on the advertisements data set are encouraging.