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Automatic Image Cropping with Aesthetic Map and Gradient Energy Map
Yueying Kao1,2; Ran He(赫然)1,2,3; Kaiqi Huang1,2,3; Huang, Kaiqi
2017-03
会议名称IEEE International Conference on Acoustics, Speech, and Signal Processing
会议录名称IEEE International Conference on Acoustics, Speech, and Signal Processing 2017
会议日期2017-3-5
会议地点NEW ORLEANS, USA
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.
关键词Image Cropping Aesthetic Map Gradient Energy Map Convolutional Neural Networks
收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/14660
专题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],2017.
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