Visual Aesthetic Quality Assessment with a Regression Model
文献类型：会议论文
| 作者 | Yueying Kao ; Chong Wang; Kaiqi Huang
|
| 出版日期 | 2015 |
| 会议日期 | 2015-09-01 |
| 会议地点 | Quebec, Canada |
| 关键词 | Agriculture feature Extraction image Analysis predictive Models quality Assessment visual Systems visualization aesthetic Image Analysis convolutional Neural Network regression |
| 页码 | 1583-1587 |
| 英文摘要 | 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. |
| 会议录 | Proc. IEEE International Conference on Image Processing 2015
 |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12677]  |
| 专题 | 自动化研究所_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 |
| 推荐引用方式 GB/T 7714 | Yueying Kao,Chong Wang,Kaiqi Huang. Visual Aesthetic Quality Assessment with a Regression Model[C]. 见:. Quebec, Canada. 2015-09-01. |
入库方式： OAI收割
来源：自动化研究所
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