Probabilistic models for region-based scene understanding
Abstract/Contents
- Abstract
- One of the long-term goals of computer vision is to be able to understand the world through visual images. This daunting task involves reasoning simultaneously about objects, regions and 3D geometry. Traditionally, computer vision research has tackled these tasks is isolation: independent detectors for finding objects, image segmentation algorithms for defining regions, and specialized monocular depth perception methods for reconstructing geometry. Unfortunately, this isolated reasoning can lead to inconsistent interpretations of the scene. In this thesis we develop a unified probabilistic model that avoids these inconsistencies. We introduce a region-based representation of the scene in which pixels are grouped together to form consistent regions. Each region is then annotated with a semantic and geometric class label. Next, we extend our representation to include the concept of objects, which can be comprised of multiple regions. Finally, we show how our region-based representation can be used to interpret the 3D structure of the scene. Importantly, we model the scene using a coherent probabilistic model over random variables defined by our region-based representation. This enforces consistency between tasks and allows contextual dependencies to be modeled across tasks, e.g., that sky should be above the horizon, and ground below it. Finally, we present an efficient algorithm for performing inference in our model, and demonstrate state-of-the-art results on a number of standard tasks.
Description
Type of resource | text |
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Form | electronic; electronic resource; remote |
Extent | 1 online resource. |
Publication date | 2010 |
Issuance | monographic |
Language | English |
Creators/Contributors
Associated with | Gould, Stephen | |
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Associated with | Stanford University, Department of Electrical Engineering | |
Primary advisor | Koller, Daphne | |
Thesis advisor | Koller, Daphne | |
Thesis advisor | Boyd, Stephen P | |
Thesis advisor | Ng, Andrew Y, 1976- | |
Advisor | Boyd, Stephen P | |
Advisor | Ng, Andrew Y, 1976- |
Subjects
Genre | Theses |
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Bibliographic information
Statement of responsibility | Stephen Gould. |
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Note | Submitted to the Department of Electrical Engineering. |
Thesis | Thesis (Ph. D.)--Stanford University, 2010. |
Location | electronic resource |
Access conditions
- Copyright
- © 2010 by Stephen Gould
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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