EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
A region-based H.263+ codec and its rate control for low VBR video
IEEE Transactions on Multimedia
Region-based rate control and bit allocation for wireless video transmission
IEEE Transactions on Multimedia
Visual sensitivity guided bit allocation for video coding
IEEE Transactions on Multimedia
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Karhunen-Loeve basis extraction and its application to images
IEEE Transactions on Image Processing
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
A robust and adaptive rate control algorithm for object-based video coding
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we proposed a method that employs the auto-scaled incremental eigenspace learning to locate the salient distortion areas continually in the video to serve the purpose of region based rate control application Compared to other locating methods, the auto-scaled incremental eigenspace learning locating method can achieve locating the salient distortion areas robustly and accurately, and specifically in real-time In addition, for the case that there exists the overlap/occlusion between different salient distortion areas, the proposed method can also obtain accurate location information which could make the region based rate control and bit allocation to reach higher efficiency in many applications The experiment results of the proposed algorithm demonstrate the subject visual quality of the video has been improved greatly.