2026-09-18T22:53:38Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/918132026-06-06T00:55:11Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Patrick Henry Winston.
Giacaglia, Giuliano Pezzolo
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-11-24T18:36:32Z
2014-11-24T18:36:32Z
2014
2014
http://hdl.handle.net/1721.1/91813
894115503
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).
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.
by Giuliano Pezzolo Giacaglia.
M.Eng.
70 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Integrating bottom-up and top-down information
Thesis
application/pdf
Publication
unknown
unknown
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<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.</Abstract>
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