کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
412042 679608 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Hypergraph based feature fusion for 3-D object retrieval
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Hypergraph based feature fusion for 3-D object retrieval
چکیده انگلیسی

In view-based 3D object retrieval, each object is represented by a set of image views. 3D object retrieval becomes a group matching problem under such definition. Recent works have shown the effectiveness of hypergraph learning that computes the distance between 3D objects by solving a hypergraph structure problem. However, the single feature used in most of state-of-the-art works is often not sufficient to describe a 3D object. In this paper, we propose a feature fusion method based on hypergraph for 3D object retrieval. Besides the frequently used Zernike moments feature, we propose a Dense Kernel Local Binary Feature (DKLBP) feature for 3D object view description. A feature fusion method is proposed under the hypgraph framework. Experiments are conducted on the popular ETH-80 and National Taiwan University 3D model datatsets. Extensive experimental results show that the proposed approach has made significant performance improvement compared to other competitive approaches in recent works.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 151, Part 2, 5 March 2015, Pages 612–619
نویسندگان
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