Integrating bottom-up and top-down information
Name
894115503-MIT.pdf
Description
Full printable version
Size
6.49 MB
Format
Adobe PDF
Checksum (MD5)
fcc27521779e2c182ccd105f45928f22
Author(s)
Giacaglia, Giuliano Pezzolo
Advisor(s)
Patrick Henry Winston.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis I present a framework for integrating bottom-up and top-down computer vision algorithms. I developed this framework, which I call the Map-Dictionary Pixel framework, because my intuition is that there is a need for tools that make it easier to build computer vision systems that mimic the way human visual systems process information. In particular, we humans humans create models of objects around us, and we use these models, top-down, to interpret, analyze and discern objects in the information that comes bottom-up from the visual world. After introducing my Map-Dictionary Pixel framework, I demonstrate how it empowers computer vision algorithms. I implement two different systems that extract the pixels of the image that correspond to a human. Even though each system uses different sets of algorithms, both use Map-Dictionary Pixel framework as the connecting pipeline. The two implementations demonstrate the utility of the Map-Dictionary Pixel framework and provide an example of how it can be used.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 69-70).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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