Component based recognition of objects in an office environment
Author(s)
Morgenstern, Christian; Heisele, Bernd
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Show full item recordAbstract
We present a component-based approach for recognizing objectsunder large pose changes. From a set of training images of a givenobject we extract a large number of components which are clusteredbased on the similarity of their image features and their locations withinthe object image. The cluster centers build an initial set of componenttemplates from which we select a subset for the final recognizer.In experiments we evaluate different sizes and types of components andthree standard techniques for component selection. The component classifiersare finally compared to global classifiers on a database of fourobjects.
Date issued
2003-11-28Other identifiers
MIT-CSAIL-TR-2003-031
AIM-2003-024
CBCL-232
Series/Report no.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
Keywords
AI, computer vision, object recognition, component object recognition