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Summary: Semantic Grouping of Visual Features
Alexandra Teynor and Hans Burkhardt
Department of Computer Science, Albert-Ludwigs-Universit¨at Freiburg, Germany
{teynor, Hans.Burkhardt}@informatik.uni-freiburg.de
Abstract
Many current object class models build on visual
parts that constitute an object. However, visually differ-
ent entities may actually refer to the same object part.
This may be harmful for part based object class mod-
els. We present a method how visually distinct parts
with the same semantic role can be associated by cre-
ating groupings based on the similarity of their occur-
rence distributions. Experimental results verify that
more compact class representations can be built based
on these groupings, which lead to improved classifica-
tion performance and/or reduced classification time.
1. Introduction
A common technique for the recognition of object
classes is the use of part dictionaries or "visual code-
books". These codebooks contain a variety of possi-
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