Robust Duplicate Detection of 2D and 3D Objects

被引：1

作者：

Vajda, Peter ^{[1
]}

Ivanov, Ivan ^{[2
]}

Goldmann, Lutz ^{[3
]}

Lee, Jong-Seok ^{[3
]}

Ebrahimi, Touradj ^{[3
]}

机构：

[1] Ecole Polytech Fed Lausanne, Prof Ebrahimis Grp, Lausanne, Switzerland

[2] Ecole Polytech Fed Lausanne, Swiss Fed Inst Technol, Multimedia Signal Proc Grp, Lausanne, Switzerland

[3] Ecole Polytech Fed Lausanne, Multimedia Signal Proc Grp MMSPG, Lausanne, Switzerland

来源：

INTERNATIONAL JOURNAL OF MULTIMEDIA DATA ENGINEERING & MANAGEMENT | 2010年 / 1卷 / 03期

基金：

瑞士国家科学基金会;

关键词：

Computer Vision; Graph; Object Duplicate Detection; Retrieval; SIFT;

D O I：

10.4018/jmdem.2010070102

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, the authors analyze their graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images to avoid explicit and complex 3D object modeling. Therefore, improved performance can be achieved in comparison to existing methods in terms of both robustness and computational complexity. Different limitations of this approach are analyzed by evaluating performance with respect to the number of training images and calculation of optimal parameters in a number of applications. Furthermore, effectiveness of object duplicate detection algorithm is measured over different object classes. The authors' method is shown to be robust in detecting the same objects even when images with objects are taken from different viewpoints or distances.

引用

页码：19 / 40

页数：22

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