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A Comparison of the Animal Recognition between the Real Objects and the Modeled 3D Objects

机译:真实对象与建模3D对象之间的动物识别的比较

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This paper proposed about comparison of the animal recognition processed on the real world objects and the modeled 3D objects. The object classification consists of the three main steps - feature extraction, training classifier and image evaluation. Feature description is based on locale visual descriptors like SIFT or SURF. Support Vector Machine (SVM) in combination with the bags of visual keypoints (BOW) is used to classify descriptors. The 3D models were created using photogrammetry and 3D modeling for ideal 3D models of mammals. This method of 3D model creation is described in details.
机译:本文提出了关于在现实世界对象和建模3D对象上处理的动物识别的比较。对象分类包括三个主要步骤 - 特征提取,培训分类器和图像评估。功能描述基于Life Visual描述符,如SIFT或SURF。支持向量机(SVM)与Visual Keypoints(Bow)的组合使用用于对描述符进行分类。使用摄影测量和3D模型来创建3D模型,以获得哺乳动物的理想3D模型。详细描述了这种3D模型创建方法。

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