Realization of affine SIFT real-time image processing for home service robot

Ying-Hao Wang, Hao-En Cheng, Chih-Jui Lin, Ri-Wei Deng, Hsuan Lee, Tzuu-Hseng S. Li
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Abstract

This paper mainly discusses the realization of affine Scale-Invariant Feature Transform (SIFT) real-time image processing method for “May” who is a home service robot designed and implemented by aiRobots laboratory. Firstly, a six-step method is proposed to create image database. Then the SIFT algorithm is adopted to detect features with this database, the error rate of features is reduced. Integration of the six-step method and SIFT can significantly decrease time for setting up the database. Thirdly, the object-recognition vision system is built up by parallel Affine-SIFT (ASIFT) algorithm, where the OpenGL is used to reduce the calculation time of affine projection and SiftGPU (Graphics Processing Unit) is adopted to accomplish the real-time operation speed of SIFT. Finally, the real-time grasping experiments demonstrate the feasibility and validity of the proposed scheme.
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家用服务机器人仿射SIFT实时图像处理的实现
本文主要讨论了仿射尺度不变特征变换(SIFT)实时图像处理方法在aiRobots实验室设计实现的家庭服务机器人“May”中的实现。首先,提出了一种六步法创建图像数据库;然后利用该数据库采用SIFT算法进行特征检测,降低了特征的错误率。将六步法与SIFT相结合,可以显著减少数据库的建立时间。第三,采用并行仿射-SIFT (ASIFT)算法构建目标识别视觉系统,采用OpenGL减少仿射投影的计算时间,采用SiftGPU(图形处理单元)实现SIFT的实时运算速度。最后,通过实时抓取实验验证了该方案的可行性和有效性。
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