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J. P. Lewis. Fast normalized cross-correlation. In Vision Interface, 1995.

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Orientation Correlation - Christmas   (Correct)

....local minima are not a problem for correlationbased methods. The Fast Fourier Transform (FFT) 24] allows fast correlation of digital signals. Correlation using the FFT was first applied to image registration by Anuta [2] A variety of improvements to correlation have been proposed over the years [17, 19, 22]. These have improved correlation results and addressed issues such as illumination invariance. Comparative studies have been made [3, 20] In the fields of computer vision and image processing robustness is important. While some of these methods claim to be robust all are based on the square ....

J.P. Lewis. Fast normalized cross-correlation. In Vison Interface, pages 120--123, 1995. http://www.idiom.com/zilla/Work/nvisionInterface/nip.html.


Robust Periodic Motion and Motion Symmetry Detection - Cutler, Davis (2000)   (Correct)

....the remaining entries can be reused (shifted) for the updated S 0 . Therefore, for each new frame, only O(N) S 0 (i; j) computations need to be done, where N is the number of rows and columns in S 0 . For computing A, the 2D FFT can be utilized to greatly decrease the computational cost [19]. Finally, SIMD instructions, such as those available on the Pentium III, can be utilized for computing S(i; j) as well as A (either directly or using the FFT) 4 Examples 4.1 Synthetic Data In this section, we demonstrate the method on synthetic data examples. We generated images of a ....

J. P. Lewis. Fast normalized cross-correlation. In Vision Interface, 1995.


Robust Real-Time Periodic Motion Detection, Analysis, and.. - Cutler, Davis (1999)   (19 citations)  (Correct)

....the remaining entries can be reused (shifted) for the updated S # . Therefore, for each new frame, only O(N) S # (i, j) computations need to be done, where N is the number of rows and columns in S # . For computing A, the 2D FFT can be utilized to greatly decrease the computational cost [18]. Finally, SIMD instructions, such as those available on the Pentium III, can be utilized for computing S # (i, j) as well as A (either directly or using the FFT) 6 Conclusions We have described new techniques to detect and analyze periodic motion as seen from both a static and moving camera. ....

J. P. Lewis. Fast normalized cross-correlation. In Vision Interface, 1995.


Learning to Track Multiple People in Omnidirectional - Video Fernando De   (Correct)

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J. P. Lewis. Fast normalized cross-correlation. In Vision Interface, 1995.


Sparse Bayesian Learning - For Efficient Visual (2005)   (Correct)

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J.P. Lewis, "Fast Normalized Cross-Correlation," Vision Interface, 1995.


Coarse-Level Object Recognition Using Interlevel Products Of - Complex Wavelets Ryan   (Correct)

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J. Lewis, "Fast normalized cross-correlation," Vision Interface, pp. 120--123, 1995.


Video Segmentation and Indexing Using Motion Estimation - Porter (2004)   (Correct)

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J. P. Lewis. Fast normalized cross-correlation. Vision Interface, pages 120--123, 1995. http://www.idiom.com/ zilla/Work/nvisionInterface/nip.html.


Epipolar Constraints for Vision-Aided Inertial Navigation - Diel, DeBitetto, Teller (2005)   (Correct)

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J. P. Lewis, "Fast normalized cross-correlation," Vision Interface, 1995.


Coarse-Level Object Recognition Using Interlevel.. - Anderson, Kingsbury.. (2005)   (Correct)

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J. Lewis, "Fast normalized cross-correlation," Vision Interface, pp. 120--123, 1995.

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