Column Time Warping with Neighborhood Distortion Cost Public

http://ir.library.oregonstate.edu/concern/honors_college_theses/m039k6655

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  • Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
  • The Cornell Laboratory of Ornithology coordinates the eBird Project in which volunteer bird watchers participate in a checklist program. Each time they go bird watching, they fill out a checklist of the number of birds of each species that they saw and upload it to a web site. This information has been used to fit models of the spatial distribution of each species of bird on a daily basis. One model pools data from many years; it provides a summary of the typical timing of bird migration each year. A second model describes the locations of the birds for each year separately. One important problem is to visualize, for each year, whether the birds are “ahead” or “behind” their typical migration timing. To do this, an algorithm was developed for “warping” the spatio-temporal distribution of the birds for a single year so that it matched the average spatio-temporal distribution. The algorithm only solves the problem approximately. The goal of this thesis was to understand the computation complexity of this time warping problem and to relate it to other known algorithms. Our analysis suggests, but does not prove, that the spatio-temporal time warping problem is computationally intractable (NP-Hard). Key Words: Time Warping, Bird Migrations, Migration Analysis
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