Visual Aesthetic Quality Assessment with a Regression Model

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	Visual Aesthetic Quality Assessment with a Regression Model
	Yueying Kao; Chong Wang; Kaiqi Huang
	2015
会议名称	IEEE International Conference on Image Processing
会议录名称	Proc. IEEE International Conference on Image Processing 2015
页码	1583-1587
会议日期	2015-09-01
会议地点	Quebec, Canada
摘要	Aesthetic image analysis has drawn much attention in recent years. However, assessing the aesthetic quality especially aesthetic score prediction is a challenging problem. In this paper, we interpret aesthetic quality assessment as a regression problem and present a new framework by directly training a regression model using a neural network. Firstly, to extract the aesthetic features which are difficult to design manually, we utilize the convolutional network to learn the features. Then, a regression model is trained based on the aesthetic features. Different from classification models which can only predict aesthetic class (high or low) in most existing works, the regression model can predict continuous aesthetic score. Experimental results on a recently published large-scale dataset show that the proposed method can assess the degree of aesthetic quality similar to human visual system effectively and outperforms the state-of-the-art methods.
关键词	Agriculture feature Extraction image Analysis predictive Models quality Assessment visual Systems visualization aesthetic Image Analysis convolutional Neural Network regression
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12677
专题	智能感知与计算研究中心
通讯作者	Kaiqi Huang
作者单位	中国科学院自动化研究所
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Yueying Kao,Chong Wang,Kaiqi Huang. Visual Aesthetic Quality Assessment with a Regression Model[C],2015:1583-1587.

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