Visual motion, stereo, texture, and symmetric boundaries are all repetition of similar patterns in time or space. These repetitions can be viewed as "echoes" of one another, and the measurement of disparities, segmentation of textons, or detection of boundary symmetries translates into detection of echo arrival periods.
Cepstral filtering, as well as Polyspectral techniques and waveform analysis, are some of the techniques used successfully for echo detection. This paper examines the application of cepstral analysis to computational vision, introduces modified improvements to the traditional methods, and provides a comparison with other routines presently used.
Finally, we introduce a general multi-evidential correlation approach which lends itself to several computational routines. CepsCorr, as we call it, is a simple general technique that can accept different matching routines, such as cepstrum and/or phase correlation as its measurement kernel. The evidences provided by each iteration of cepsCorr can then be combined to provide a more accurate estimate of motion or binocular disparity.
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