Object recognition is a central problem in computer vision which deals with both localizing and identifying objects in images. Object proposals have recently become an important part of the object recognition process. Object proposals are algorithms used for localizing objects in images. This thesis is a study in object proposals and is composed of three parts. First, we present a new data-driven approach for generating object proposals. Second, we release a MATLAB library which can be used to generate object proposals using all the existing algorithms. The library can also be used for evaluating object proposals using the three most commonly used metrics. Finally, we identify previously unnoticed bias in the existing protocol for evaluating object proposals and propose ways to alleviate this bias. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/56590 |
| Date | 09 September 2015 |
| Creators | Chavali, Neelima |
| Contributors | Electrical and Computer Engineering, Batra, Dhruv, Parikh, Devi, Abbott, A. Lynn |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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