Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Image Registration Using Wavelet-Based Motion Model
International Journal of Computer Vision
Layered 4D Representation and Voting for Grouping from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Subtly Different Facial Expression Recognition and Expression Intensity Estimation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Voting-Based Computational Framework for Visual Motion Analysis and Interpretation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Subtle facial expression recognition using motion magnification
Pattern Recognition Letters
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A motion estimation algorithm using wavelet approximation as an optical flow model has been developed to estimate accurate dense optical flow from an image sequence. This wavelet motion model is particularly useful in estimating optical flows with large displacement. Traditional pyramid methods which use the coarse-to-fine image pyramid by image burring in estimating optical flow often produce incorrect results when the coarse-level estimates contain large errors that cannot be corrected at the subsequent finer levels. This happens when regions of low texture become flat or certain patterns result in spatial aliasing due to imageblurring. Our method, in contrast, uses large-to-small full-resolution regions without blurring images, and simultaneously optimizes the coarser and finer parts of optical flow so that the large and small motion can be estimated correctly. We compare results obtained by using our method with those obtained by using one of the leading optical flow methods, the Szeliski pyramid spline-based method. The experiments include cases of small displacement (less than4 pixels under 128 脳 128 image size or equivalent displacement under other image sizes), and those of large displacement (10 pixels). While both methods produce comparableresults when the displacements are small, our method out performs pyramid spline-based method when the displacements are large.