On the estimation of optical flow: relations between different approaches and some new results
Artificial Intelligence
A Frequency Domain Algorithm for Multiframe Detection and Estimation of Dim Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of component image velocity from local phase information
International Journal of Computer Vision
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distributed representation and analysis of visual motion
Distributed representation and analysis of visual motion
Steerable filters and local analysis of image structure
Steerable filters and local analysis of image structure
Image-flow computation: an estimation-theoretic framework and a unified perspective
CVGIP: Image Understanding
Performance of optical flow techniques
International Journal of Computer Vision
Techniques and standards for image, video, and audio coding
Techniques and standards for image, video, and audio coding
The Frequency Structure of One-Dimensional Occluding Image Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Processing and Communications
Video Processing and Communications
Generalized image matching by the method of differences
Generalized image matching by the method of differences
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
Steerable wedge filters for local orientation analysis
IEEE Transactions on Image Processing
Estimation of Multiple Accelerated Motions Using Chirp-Fourier Transform and Clustering
IEEE Transactions on Image Processing
Computer Vision and Image Understanding
Estimation of motions in color image sequences using hypercomplex fourier transforms
IEEE Transactions on Image Processing
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We extend the mathematical analysis of previous work [M.T. Andersson, Controllable multi-dimensional filters and models in low-level computer vision, Ph.D. Thesis, Department of Electrical Engineering, Linkonping University, Sweden, 1992] and we give rigorous, general, mathematical formulas for the construction of 3-D steerable directional cosine filters of arbitrary higher order. Furthermore, we present the mathematical analysis for the construction of arbitrary narrow, steerable directional quadrature pairs. Incorporating the ''Donut Mechanism'' of Simoncelli [E.P. Simoncelli, Distributed representation and analysis of visual motion, Ph.D. Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 1993] and extending it for quadrature pairs, we present a unified theory and a simple algorithm for using the constructed filters to estimate the motion in image sequences. Based on simple theoretical analysis, we explain the advantages of using higher order filters. Experimental results on synthetic, realistic, and natural sequences verify the effectiveness of the main algorithm and our arguments.