The scene partitioning problem is to delineate regions in an image that correspond to the same object according to some underlying object model. Examples include partitioning an intensity image into piecewise constant intensities or identifying separate planar regions in a disparity map. A general algorithm for solving the partitioning problem in cases of linear models is presented. The algorithm uses a statistical test in a region growing formalism. The algorithm relies on the assumption that the correct image partition is connected in image coordinates. Experiments are performed on a series of models with a range of state dimensions.
Title
Scene Partitioning via Statistic-Based Region Growing
Published
1905-06-16
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Other Identifiers
CSD-94-817
Type
Text
Extent
13 p
Archive
The Engineering Library
Usage Statement
Researchers may make free and open use of the UC Berkeley Library’s digitized public domain materials. However, some materials in our online collections may be protected by U.S. copyright law (Title 17, U.S.C.). Use or reproduction of materials protected by copyright beyond that allowed by fair use (Title 17, U.S.C. § 107) requires permission from the copyright owners. The use or reproduction of some materials may also be restricted by terms of University of California gift or purchase agreements, privacy and publicity rights, or trademark law. Responsibility for determining rights status and permissibility of any use or reproduction rests exclusively with the researcher. To learn more or make inquiries, please see our permissions policies (https://www.lib.berkeley.edu/about/permissions-policies).
