Hierarchical mixtures of experts and the EM algorithm
Neural Computation
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Automatic thumbnail cropping and its effectiveness
Proceedings of the 16th annual ACM symposium on User interface software and technology
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic image retargeting with fisheye-view warping
Proceedings of the 18th annual ACM symposium on User interface software and technology
MUM '05 Proceedings of the 4th international conference on Mobile and ubiquitous multimedia
Seam carving for content-aware image resizing
ACM SIGGRAPH 2007 papers
Region-based visual attention analysis with its application in image browsing on small displays
Proceedings of the 15th international conference on Multimedia
Improved seam carving for video retargeting
ACM SIGGRAPH 2008 papers
Optimized scale-and-stretch for image resizing
ACM SIGGRAPH Asia 2008 papers
Image description using joint distribution of filter bank responses
Pattern Recognition Letters
Fast structure-preserving image retargeting
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A smart automatic thumbnail cropping based on attention driven regions of interest extraction
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Image retargeting based on global energy optimization
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
An automatic image browsing technique for small display users
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Salient region detection and segmentation
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
Image retargeting using importance diffusion
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Saliency detection for content-aware image resizing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Nonhomogeneous scaling optimization for realtime image resizing
The Visual Computer: International Journal of Computer Graphics
A comparative study of image retargeting
ACM SIGGRAPH Asia 2010 papers
Affective saliency map considering psychological distance
Neurocomputing
A subjective method for image segmentation evaluation
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Temporal Spectral Residual for fast salient motion detection
Neurocomputing
Self-Adaptive Image Cropping for Small Displays
IEEE Transactions on Consumer Electronics
Unsupervised extraction of visual attention objects in color images
IEEE Transactions on Circuits and Systems for Video Technology
Multi-spectral saliency detection
Pattern Recognition Letters
Multi-spectral dataset and its application in saliency detection
Computer Vision and Image Understanding
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Content-aware image resizing has been a promising theme in the communities of image processing and computer vision. To the best of our knowledge, most existing methods for image resizing are unsupervised. These unsupervised methods may either fail to protect the interesting regions or cause distortion of the image structure. This paper presents a novel learning based method for seam carving by incorporating the learned boundary of the important content. Specifically, a novel boundary model of the region of interest (ROI) is learned on a set of training images at first. Then the boundary of an input image is utilized as a key prior in performing seam carving to obtain the target image. The proposed method for image resizing can generate much less seams cutting through the ROI compared with previous efforts toward the same goal. Thus, the desirable regions can be preserved in the target image and the structural consistency of the input image is naturally maintained. Experiments on two publicly available data sets demonstrate the effectiveness of the proposed method.