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UBC Theses and Dissertations
Odmas : object discovery through motion, appearance and shape Southey, Tristram
Abstract
In this thesis we examine the problem of Object Discovery, the autonomous acquisition of object models, using a combination of shape, appearance and motion. We propose a new technique for detecting rigidly moving objects and constructing models of their appearance and shape called the ODMAS (Object .Discovery through Motion, Appearance and Shape) system. Our technique is a multi-stage approach. First, a stereo camera is used to find a sequence of images and shape maps of a given scene. Then the scene is oversegmented using normalized cuts based on a combination of shape and appearance. SIFT image features are matched between sequential pairs of images to identify groups of moving features and the three dimensional location of these moving features in the scene is identified using the shape map from the stereo camera. The moving features are then further individuated into objects by identifying groups where the motion of the features is rigid. These rigid feature groups are used to determine which regions in the segmentation of the scene correspond to objects, grouping together oversegmented regions as necessary. Additional features are extracted from these regions and combined with the rigidly moving image features to create snapshots of the object's appearance and shape. Finally, these snapshots are grouped together over time to produce models of the objects.
Item Metadata
Title |
Odmas : object discovery through motion, appearance and shape
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2005
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Description |
In this thesis we examine the problem of Object Discovery, the autonomous
acquisition of object models, using a combination of shape, appearance and
motion. We propose a new technique for detecting rigidly moving objects and
constructing models of their appearance and shape called the ODMAS (Object
.Discovery through Motion, Appearance and Shape) system. Our technique is
a multi-stage approach. First, a stereo camera is used to find a sequence of
images and shape maps of a given scene. Then the scene is oversegmented using
normalized cuts based on a combination of shape and appearance. SIFT image
features are matched between sequential pairs of images to identify groups of
moving features and the three dimensional location of these moving features in
the scene is identified using the shape map from the stereo camera. The moving
features are then further individuated into objects by identifying groups where
the motion of the features is rigid. These rigid feature groups are used to determine
which regions in the segmentation of the scene correspond to objects,
grouping together oversegmented regions as necessary. Additional features are
extracted from these regions and combined with the rigidly moving image features
to create snapshots of the object's appearance and shape. Finally, these
snapshots are grouped together over time to produce models of the objects.
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Genre | |
Type | |
Language |
eng
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Date Available |
2009-12-15
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0051717
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2005-11
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.