Research in Algorithms for Geometric Pattern Matching MIT 2001 - 06 Progress Report : November 1 , 2001 — December 31 , 2001 Piotr
نویسنده
چکیده
Frechet distance is one of the most fundamental measures used to compute dissimilarity between two sequences of points (e.g., between two signatures recorded by an electronic pen). It is often referred to as the “dog-leash” distance. This is because it corresponds to the minimal length of a “leash” so that a dog and its owner can traverse their respective sequences from beginning to end, while respecting the constraint that at any moment of time, the distance between them cannot exceed the leash length. See Project Proposal for formal definition.
منابع مشابه
Research in Algorithms for Geometric Pattern Matching MIT 2001 - 06 Progress Report : July 1 , 2002 – December 31 , 2002 Piotr
As mentioned earlier, the focus of this project is to design a fast similarity search algorithm for large data sets of images. To evaluate the similarity between images, we use the Earth-Mover Metric (EMD). It was experimentally verified to capture well the perceptual notion of a difference between images, in fact much better than other wellknown metrics (e.g., Euclidean distance between the fe...
متن کاملResearch in Algorithms for Geometric Pattern Matching MIT 2001 - 06 Progress Report : January 1 , 2002 – June 30 , 2002
During the period of January-June 2002, the main focus of this project was implementing and evaluating algorithms for embedding Earth-Mover Distance into the Euclidean space. Earth-mover distance (EMD) is a recently proposed metric for computing distance between features of images (see [EMD] and references therein). It was experimentally verified to capture well the perceptual notion of a diffe...
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