Automatic Image Cropping with Aesthetic Map and Gradient Energy Map
文献类型：会议论文
| 作者 | Yueying Kao1,2; Ran He(赫然)1,2,3 ; Kaiqi Huang1,2,3; Huang, Kaiqi
|
| 出版日期 | 2017-03 |
| 会议日期 | 2017-3-5 |
| 会议地点 | NEW ORLEANS, USA |
| 关键词 | Image Cropping Aesthetic Map Gradient Energy Map Convolutional Neural Networks |
| 英文摘要 |
Image cropping is a fundamental task in image editing to
enhance the aesthetic quality of images. In this paper,
we propose an automatic image cropping technique based
on aesthetic map and gradient energy map. Instead of
utilizing aesthetic rules in previous methods, we learn the
aesthetic map by a deep convolutional neural network with
a large-scale dataset for aesthetic quality assessment. The
aesthetic map can highlight the discriminative image regions
for high (or low) aesthetic quality category. The gradient
energy map presents edge spatial distribution of images
and is developed to compute the simplicity of images.
Then a composition model is learned with the aesthetic
map and gradient energy map to evaluate the quality of
composition for crops. Moreover, an aesthetic preservation
model is developed to compute the aesthetic information
remained in crops to avoid cropping out high aesthetic
regions. Experiments show that our approach significantly
outperforms state-of-the-art cropping methods. |
| 会议录 | IEEE International Conference on Acoustics, Speech, and Signal Processing 2017
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14660]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Huang, Kaiqi |
| 作者单位 | 1.CRIPAC & NLPR, CASIA 2.University of Chinese Academy of Sciences 3.CAS Center for Excellence in Brain Science and Intelligence Technology |
| 推荐引用方式 GB/T 7714 | Yueying Kao,Ran He,Kaiqi Huang,et al. Automatic Image Cropping with Aesthetic Map and Gradient Energy Map[C]. 见:. NEW ORLEANS, USA. 2017-3-5. |
入库方式： OAI收割
来源：自动化研究所
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