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dc.contributor.authorSaitwal, Kishor
dc.contributor.authorRoberts, Rodney G.
dc.contributor.authorBalakrishnan, Venkataramanan
dc.contributor.authorMaciejewski, Anthony A.
dc.contributor.authorChang, Chu-Yin
dc.date.accessioned2007-01-03T08:09:35Z
dc.date.available2007-01-03T08:09:35Z
dc.date.issued2006
dc.descriptionIncludes bibliographical references (pages 29-30).
dc.description.abstractEigendecomposition-based techniques are popular for a number of computer vision problems, e.g., object and pose estimation, because they are purely appearance based and they require few on-line computations. Unfortunately, they also typically require an unobstructed view of the object whose pose is being detected. The presence of occlusion and background clutter precludes the use of the normalizations that are typically applied and significantly alters the appearance of the object under detection. This work presents an algorithm that is based on applying eigendecomposition to a quadtree representation of the image dataset used to describe the appearance of an object. This allows decisions concerning the pose of an object to be based on only those portions of the image in which the algorithm has determined that the object is not occluded. The accuracy and computational efficiency of the proposed approach is evaluated on 16 different objects with up to 50% of the object being occluded and on images of ships in a dockyard.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationChang, Chu-Yin, et al., Quadtree-Based Eigendecomposition for Pose Estimation in the Presence of Occlusion and Background Clutter, Pattern Analysis and Applications 10, no. 2 (February 2007): [15]-31.
dc.identifier.urihttp://hdl.handle.net/10217/67372
dc.languageEnglish
dc.publisherColorado State University. Libraries
dc.publisher.originalSpringer-Verlag London Limited
dc.relation.ispartofFaculty Publications - Department of Electrical and Computer Engineering
dc.rights©2006 Springer-Verlag London Ltd.
dc.subjectpartial occlusion
dc.subjectbackground clutter
dc.subjectsingular value decomposition
dc.subjectobject recognition
dc.subjectpose estimation
dc.subjectquadtree decomposition
dc.titleQuadtree-based eigendecomposition for pose estimation in the presence of occlusion and background clutter
dc.typeText


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