15 March 1994 Optical flow methods for tracking problems
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Results are presented of a numerical survey of optical flow algorithms for tracking problems associated with infrared imaging in high-speed missiles. The algorithms tested include those associated with normal flow subject to global smoothness constraints, edge detection via zero crossings of the image after convolution with spatiotemporal filters, and windowed matching techniques. The tracking problems considered in this survey fall into two classes: acquisition, and tracking after acquisition. These classes can be further divided into near and far range problems, characterized by extended and point target images. Other parameters of interest model allowable target and sensors motion and the amount of background clutter. Each of the above methods for determining optical flow can be used in conjunction with a variety of image preprocessing techniques such as kernel smoothing (especially by Gaussian kernels). and evolution under affine invariant partial differential operators. These preprocessing methods can also by used in combination with other approaches such as temporal layering in which successive image are combined to produce images with streaks whose edges are predominantly parallel to the optical flow.
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Charles Kenney, Charles Kenney, Gary A. Hewer, Gary A. Hewer, Wei Kuo, Wei Kuo, "Optical flow methods for tracking problems", Proc. SPIE 2242, Wavelet Applications, (15 March 1994); doi: 10.1117/12.170057; https://doi.org/10.1117/12.170057

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