کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
526343 869096 2008 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Learning function-based object classification from 3D imagery
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Learning function-based object classification from 3D imagery
چکیده انگلیسی

We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical description of object classes is constructed. The object classes are described in terms of functional components. The multi-level hierarchy is designed and constructed using a large set of signature-based reasoning and grading mechanisms. This set employs likelihood functions that are built as radial-based functions from the histograms of the object instances. During classification, a probabilistic matching measure is used to search through a finite graph to find the best assignment of geometric parts to the functional structures of each class. An object is assigned to the class that provides the highest matching value. Reuse of functional primitives in different classes enables easy expansion to new categories. We tested the proposed scheme on a database of about 1000 different 3D objects. The proposed scheme achieved high classification accuracy while using small training sets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 110, Issue 2, May 2008, Pages 173–191
نویسندگان
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