A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skin Detection in Video under Changing Illumination Conditions
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
A fast algorithm to find the region-of-interest in the compressed MPEG domain
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
An Efficient Graphical Shot Verifier Incorporating Visual Rhythm
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Foveated video quality assessment
IEEE Transactions on Multimedia
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
ROI video coding based on H.263+ with robust skin-color detection technique
IEEE Transactions on Consumer Electronics
Face localization and authentication using color and depth images
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Parabolic Motion-Vector Re-estimation Algorithm for Compressed Video Downscaling
Journal of Signal Processing Systems
Discrimination of media moments and media intervals: sticker-based watch-and-comment annotation
Multimedia Tools and Applications
Discriminative two-level feature selection for realistic human action recognition
Journal of Visual Communication and Image Representation
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Region-of-interest (ROI) determination is very important for video processing and it is desirable to find a simple method to identify the ROI. Along this direction, this paper investigates a user attention model based on visual rhythm analysis for automatic determination of ROI in a video. The visual rhythm, which is an abstraction of a video, is a thumbnail version of a video by a 2-D image that captlIres the temporal information of a video sequence. Four sampling lines, including diagonal, anti-diagonal, vertical, and horizontal lines, are employed to obtain four visual rhythm maps in order to analyze the location of the ROI from video data. Via the variation on visual rhythms, object and camera motions can be efficiently distinguished. As for hardware design consideration, the proposed scheme can accurately extract ROI with very low computational complexity for real-time applications. The promising results from the experiments demonstrate that the moving object is effectively and efficiently extracted. Finally, we present a way to use flexible macroblock ordering in combination with ROI determination as a preprocessing step for H.264/AVC video coding, and experimental results show the quality of ROI regions is significantly enhanced.