Robot target recognition and tracking based on panoramic vision

Yanhua Liang, Chengtao Cai
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Abstract

Aiming at the problem of the algorithm of target recognition based on SIFT(Scale invariant feature transform) feature matching is poor at celerity and the algorithm of target tracking based on the target's color feature is easily affected by outside. A target recognition algorithm based on SIFT which based on color guide and a target tracking algorithms based on compressed sensing theory is presented. According to the color image information such as pre-preprocessing identification, identification of the target region, Obtained according to pretarget template, after recognition of the pre-image for SIFT feature matching, can be more accurately identify the target, and determines the target pixel coordinates in the image according to the determined target pixel coordinate. Used compressed sensing target tracking algorithm, you can target the implementation of tracking. The experiments prove that these two algorithms can be applied to panoramic visual object recognition and tracking.
基于全景视觉的机器人目标识别与跟踪
针对基于SIFT(Scale invariant feature transform,尺度不变特征变换)的目标识别算法特征匹配快速性差以及基于目标颜色特征的目标跟踪算法易受外界影响的问题。提出了一种基于颜色导向的SIFT目标识别算法和一种基于压缩感知理论的目标跟踪算法。根据彩色图像信息等进行预处理识别,对目标区域进行识别,根据预目标模板获得,识别后的预图像进行SIFT特征匹配,可以更准确地识别目标,并根据确定的目标像素坐标确定图像中的目标像素坐标。采用压缩感知目标跟踪算法,可以实现目标跟踪。实验证明,这两种算法可以应用于全景视觉目标的识别和跟踪。
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