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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01r494vn61z
Title: Implementation, Testing, and Comparison of Feature Detection Algorithms for Micro-GPS
Authors: Margulies, Rachel
Advisors: Rusinkiewicz, Szymon
Department: Computer Science
Class Year: 2016
Abstract: Micro-GPS – proposed by Rusinkiewicz and Finkelstein – would provide the world with subcentimeter location determination, simply by finding identifying features in the textures of the ground. Micro-GPS opens up wide-ranging applications, including automated lane control for cars, robot navigation in warehouses, among many others. In this thesis, I implement and evaluate four different feature detection algorithms, to determine which – if any – are best suited to the needs of the larger Micro-GPS project. One of the most significant outcomes of this research project is the multi-step testing suite I have developed for assessing existing and future data sets. Based upon the results of the testing suite, I propose that Difference-of-Gaussians blob detection should be the primary algorithm used for the Micro-GPS project, though Canny edge detection could be used in conjunction to find appropriate parameters.
Extent: 70 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01r494vn61z
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Computer Science, 1988-2016

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