用于目标识别和姿态估计的Patch-duplets

B. Johansson, A. Moe
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引用次数: 29

摘要

本文描述了一种基于视图的目标识别方法,并从单幅图像中估计目标姿态。该方法基于特征向量匹配和聚类。检测一组兴趣点并将其组合成对。从局部定向图像中提取以每个点为中心的一对补丁。补丁的方向和大小取决于点的相对位置,这使得它们不受平移、旋转和局部缩放的影响。每对补丁构成一个特征向量。在多幅真实图像上对该方法进行了验证,并与SIFT特征进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patch-duplets for object recognition and pose estimation
This paper describes a view-based method for object recognition and estimation of object pose from a single image. The method is based on feature vector matching and clustering. A set of interest points is detected and combined into pairs. A pair of patches, centered around each point in the pair, is extracted from a local orientation image. The patch orientation and size depends on the relative positions of the points, which make them invariant to translation, rotation, and locally invariant to scale. Each pair of patches constitutes a feature vector. The method is demonstrated on a number of real images and the patch-duplet feature is compared to the SIFT feature.
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