Robust regression and outlier detection
Robust regression and outlier detection
Key to effective video retrieval: effective cataloging and browsing
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
An Invitation to 3-D Vision: From Images to Geometric Models
An Invitation to 3-D Vision: From Images to Geometric Models
Estimation of Arbitrary Camera Motion in MPEG Videos
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Camera Motion Analysis in On-line MPEG Sequences
WIAMIS '07 Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services
Particle Video: Long-Range Motion Estimation Using Point Trajectories
International Journal of Computer Vision
Efficient, robust, and fast global motion estimation for video coding
IEEE Transactions on Image Processing
Robust Global Motion Estimation Oriented to Video Object Segmentation
IEEE Transactions on Image Processing
A fully automated content-based video search engine supporting spatiotemporal queries
IEEE Transactions on Circuits and Systems for Video Technology
Rapid estimation of camera motion from compressed video with application to video annotation
IEEE Transactions on Circuits and Systems for Video Technology
VISON: VIdeo Summarization for ONline applications
Pattern Recognition Letters
Rapid cut detection on compressed video
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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The estimation of camera motion is one of the most important aspects for video processing, analysis, indexing, and retrieval. Most of existing techniques to estimate camera motion are based on optical flow methods in the uncompressed domain. However, to decode and to analyze a video sequence is extremely time-consuming. Since video data are usually available in MPEG-compressed form, it is desirable to directly process video material without decoding. In this paper, we present a novel approach for estimating camera motion in MPEG video sequences. Our technique relies on linear combinations of optical flow models. The proposed method first creates prototypes of optical flow, and then performs a linear decomposition on the MPEG motion vectors, which is used to estimate the camera parameters. Experiments on synthesized and real-world video clips show that our technique is more effective than the state-of-the-art approaches for estimating camera motion in MPEG video sequences.