A study on the feature matching performance of randomized trees

Yong Tian Wang; Jing Dun Lin; Jing Chen; Jun Wei Guo; Wei Liu; Kang Xue

A study on the feature matching performance of randomized trees

Yong Tian Wang^*, Jing Dun Lin, Jing Chen, Jun Wei Guo, Wei Liu, Kang Xue

^*此作品的通讯作者

光电学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

4 引用（Scopus）

摘要

In order to improve the augmented reality systems, is presented an evaluation of the randomized tree algorithm for augmented reality feature matching, and compared it with the scale-invariant feature transform algorithm. Tests including the adaptability and matching speed on rotation, scale and illumination changes were carried out. Experimental results showed that random tree can achieve 30 frames per second of real-time feature matching, and moreover, can reach more than 50% of the matching rate when illumination changes, however its matching accuracy still needs to be improved.

源语言	英语
页（从-至）	988-993
页数	6
期刊	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
卷	29
期	11
出版状态	已出版 - 11月 2009

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AU - Lin, Jing Dun

AU - Chen, Jing

AU - Guo, Jun Wei

AU - Liu, Wei

AU - Xue, Kang

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N2 - In order to improve the augmented reality systems, is presented an evaluation of the randomized tree algorithm for augmented reality feature matching, and compared it with the scale-invariant feature transform algorithm. Tests including the adaptability and matching speed on rotation, scale and illumination changes were carried out. Experimental results showed that random tree can achieve 30 frames per second of real-time feature matching, and moreover, can reach more than 50% of the matching rate when illumination changes, however its matching accuracy still needs to be improved.

AB - In order to improve the augmented reality systems, is presented an evaluation of the randomized tree algorithm for augmented reality feature matching, and compared it with the scale-invariant feature transform algorithm. Tests including the adaptability and matching speed on rotation, scale and illumination changes were carried out. Experimental results showed that random tree can achieve 30 frames per second of real-time feature matching, and moreover, can reach more than 50% of the matching rate when illumination changes, however its matching accuracy still needs to be improved.

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KW - Feature matching

KW - Randomized tree

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A study on the feature matching performance of randomized trees

摘要

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