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Methodology for the objects recognition in range images using Kinect sensor

机译:使用Kinect传感器的范围图像中对象识别的方法

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This paper presents the methodology used for the detection and recognition of some objects from the analysis of range images obtained from the Kinect sensor. Thus, is carried out the integration of a number of methodologies that are used daily in processes of vision and artificial intelligence, and from these, are intended to illustrate how efficient it can be the right choice of existing methods for the best results. In the segmentation stage it has been used the well-known Maximally-stable Extremal Region Extraction Algorithm, then, geometric characteristics of each object are extracted, and an evaluation is made of different classifiers. After the experimental tests it was possible to obtain a recognition rate of 99.4% through a multilayer perceptron neural network. All processing is performed using the openCV and openNI libraries.
机译:本文介绍了用于从基于Kinect传感器获得的范围图像的分析中检测和识别某些物体的方法。因此,进行了许多在视觉和人工智能过程中使用的多种方法的集成,并且来自这些方法,旨在说明最佳结果的现有方法的正确选择有效程度。在分割阶段,它已经使用了众所周知的最大稳定的极值提取算法,然后提取每个对象的几何特征,并且评估由不同的分类器制成。在实验测试之后,可以通过多层的感知性神经网络获得99.4%的识别率。所有处理都使用OpenCV和OpenNi库进行。

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