MPI parallel implementation of 3D object categorization using spin-images

A. Eleliemy, D. Hegazy, W. Elkilani
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引用次数: 4

Abstract

Object recognition and categorization are two important key features of computer vision. Accuracy aspects represent research challenge fo r both object recognition and categorization techniques. High performance computing (HPC) technologies usually manage the increasing time and complexity of computations. In this paper, a new approach that use 3D spin-images for 3D object categorization is introduced. The main contribution of our approach i s that it employs the MPI techniques in a unique way to extract spin-images. The technique proposed utilizes the independence between spin-images generated at each point. Time estimation of our technique ha ve shown dramatic decrease of the categorization time proportional to number of workers used.
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基于自旋图像的三维物体分类的MPI并行实现
目标识别和分类是计算机视觉的两个重要特征。准确性方面是目标识别和分类技术的研究挑战。高性能计算(HPC)技术通常用于管理不断增加的计算时间和复杂性。本文介绍了一种利用三维自旋图像进行三维物体分类的新方法。我们的方法的主要贡献在于它以一种独特的方式使用MPI技术来提取自旋图像。该技术利用了每个点产生的自旋图像之间的独立性。我们的技术的时间估计已经显示出分类时间与使用的工人数量成比例的急剧减少。
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