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Full-Text Articles in Physical Sciences and Mathematics
Learning From One Example In Machine Vision By Sharing Probability Densities, Erik Learned-Miller
Learning From One Example In Machine Vision By Sharing Probability Densities, Erik Learned-Miller
Erik G Learned-Miller
Human beings exhibit rapid learning when presented with a small number of images of a new object. A person can identify an object under a wide variety of visual conditions after having seen only a single example of that object. This ability can be partly explained by the application of previously learned statistical knowledge to a new setting. This thesis presents an approach to acquiring knowledge in one setting and using it in another. Specifically, we develop probability densities over common image changes. Given a single image of a new object and a model of change learned from a different …
Transform-Invariant Image Decomposition With Similarity Templates, Chris Stauffer, Erik Learned-Miller, Kinh Tieu
Transform-Invariant Image Decomposition With Similarity Templates, Chris Stauffer, Erik Learned-Miller, Kinh Tieu
Erik G Learned-Miller
Recent work has shown impressive transform-invariant modeling and clustering for sets of images of objects with similar appearance. We seek to expand these capabilities to sets of images of an object class that show considerable variation across individual instances (e.g. pedestrian images) using a representation based on pixel-wise similarities, similarity templates. Because of its invariance to the colors of particular components of an object, this representation enables detection of instances of an object class and enables alignment of those instances. Further, this model implicitly represents the regions of color regularity in the class-specific image set enabling a decomposition of that …