A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
A Coherent Computational Approach to Model Bottom-Up Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual attention detection in video sequences using spatiotemporal cues
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
A Visual Attention Based Region-of-Interest Determination Framework for Video Sequences*
IEICE - Transactions on Information and Systems
Rapid Biologically-Inspired Scene Classification Using Features Shared with Visual Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Visual Attention Map for Compressed Video
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
Real-time spatiotemporal segmentation of video objects in the H.264 compressed domain
Journal of Visual Communication and Image Representation
Selective Extraction of Visual Saliency Objects in Images and Videos
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 01
Optimized scale-and-stretch for image resizing
ACM SIGGRAPH Asia 2008 papers
Biologically Motivated Salient Regions Detection Approach
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 02
Object motion detection using information theoretic spatio-temporal saliency
Pattern Recognition
Pulse discrete cosine transform for saliency-based visual attention
DEVLRN '09 Proceedings of the 2009 IEEE 8th International Conference on Development and Learning
Salient region detection by modeling distributions of color and orientation
IEEE Transactions on Multimedia
Spatiotemporal Saliency in Dynamic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
An automatic image browsing technique for small display users
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Interest point detection and scale selection in space-time
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
IEEE Transactions on Image Processing
Resizing by symmetry-summarization
ACM SIGGRAPH Asia 2010 papers
Key frame extraction based on visual attention model
Journal of Visual Communication and Image Representation
Image Signature: Highlighting Sparse Salient Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Visual Communication and Image Representation
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
Automatic foveation for video compression using a neurobiological model of visual attention
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Global motion estimation from coarsely sampled motion vector field and the applications
IEEE Transactions on Circuits and Systems for Video Technology
Video Adaptation for Small Display Based on Content Recomposition
IEEE Transactions on Circuits and Systems for Video Technology
An Efficient Spatiotemporal Attention Model and Its Application to Shot Matching
IEEE Transactions on Circuits and Systems for Video Technology
Non-local spatial redundancy reduction for bottom-up saliency estimation
Journal of Visual Communication and Image Representation
Visual attention modeling based on short-term environmental adaption
Journal of Visual Communication and Image Representation
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In this study, a spatiotemporal saliency detection and salient region determination approach for H.264 videos is proposed. After Gaussian filtering in Lab color space, the phase spectrum of Fourier transform is used to generate the spatial saliency map of each video frame. On the other hand, the motion vector fields from each H.264 compressed video bitstream are backward accumulated. After normalization and global motion compensation, the phase spectrum of Fourier transform for the moving parts is used to generate the temporal saliency map of each video frame. Then, the spatial and temporal saliency maps of each video frame are combined to obtain its spatiotemporal saliency map using adaptive fusion. Finally, a modified salient region determination scheme is used to determine salient regions (SRs) of each video frame. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of two comparison approaches.