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Title: Robust Global Motion Estimation From Mpeg Streamswith a Gradient Based Refinement
Other Titles: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)
Author's Homepage:
Keywords: data compression
gradient methods
image segmentation
image sequences
motion estimation
parameter estimation
video coding
video streaming
Electronic & Electrical Engineering
Issue Date: 2006
Publisher: IEEE
Citation: Corrigan, D.; Kokaram, A.; Coudray, R.; Besserer, B., Robust Global Motion Estimation From Mpeg Streamswith a Gradient Based Refinement, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), Toulouse, 14-19th May, 2, IEEE, 2006, II - II
Series/Report no.: 2
Abstract: In this paper a new robust algorithm for global motion estimation from an MPEG stream is proposed. The approach is to use a hybrid of two previous global motion estimation algorithms in order to improve the accuracy and robustness of the estimate. The first algorithm is a non-parametric technique which uses the block based motion vectors obtained from an MPEG2 stream and which also generates a coarse background segmentation of the frame. The second algorithm is a gradient based technique which estimates the parameters from the image data directly. In this work, an initial estimate for the global motion is obtained using the non-parametric approach. The parameters are then refined using the gradient based estimation and the segmentation field. This hybrid approach shows significant reduction in mean compensation error over the non-parametric approach. The algorithm is then applied to the problem of mosaicking in sports sequences in which the global motion parameters can be used to make a panorama of an entire shot
Description: PUBLISHED
Appears in Collections:Electronic & Electrical Eng (Scholarly Publications)

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