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Robot vision using a feature search strategy generated from a 3D object model

机译:使用从3D对象模型生成的特征搜索策略的机器人视觉

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摘要

A robot vision system that automatically generates an object recognition strategy from a 3D model and recognizes the object using this strategy is presented. The appearance of an object from various viewpoints is described in terms of visible 2D features such as parallel lines and ellipses. Features are then ranked according to the number of viewpoints from which they are visible. The rank and feature extraction cost of each feature are used to generate a treelike strategy graph. This graph gives an efficient feature search order when the viewpoint is unknown, starting with commonly occurring features and ending with features specific to a certain viewpoint. The system searches for features in the order indicated by the graph. After detection, the system compares a lines representation generated from the 3D model with the image features to localize the object. Perspective projection is used in the localization process to obtain the precise position and attitude of the object, whereas orthographic projection is used in the strategy generation process to allow symbolic manipulation. Experimental results are given.
机译:提出了一种机器人视觉系统,该系统可自动从3D模型生成对象识别策略并使用该策略识别对象。从可见的2D特征(例如平行线和椭圆)描述了从各种角度看物体的外观。然后根据可见视点的数量对它们进行排序。每个特征的等级和特征提取成本用于生成树状策略图。当视点未知时,此图给出了有效的特征搜索顺序,从常见特征开始,到特定于特定视点的特征结束。系统以图形指示的顺序搜索特征。检测后,系统会将3D模型生成的线条表示与图像特征进行比较,以定位对象。透视投影用于定位过程中以获取对象的精确位置和姿态,而正交投影用于策略生成过程中以进行符号操作。给出了实验结果。

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