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A Cognitive Framework on Object Recognition and Localization for Robotic Vision

机译:机器人视觉目标识别与定位的认知框架

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The main aim of this work is to develop an algorithm for object recognition and localization with application to automatons. The algorithm development is done in three phases: Initially, the algorithm for object detection is framed which in result gives us segmented object matrices. Secondly, the object recognition algorithm is framed which in result gives the object label of recognized object. Thirdly, the position of recognized object is found out from object localization algorithm. Vision is vital for the functioning of robots in amorphous surroundings. In an aim of simplifying the interactions between human and robots as well as to carry out the more complex operations, cognitive abilities such as visual perception are appended to the systems for the sake of intelligent operations. The consolidated developed algorithm will recognize the desired object and also gives its location in the world coordinate system. The algorithm developed in this paper proves to be good and fast as we achieve the accuracy of 100% in object detection as well as in recognition algorithm and 98.03% to 99.99% accuracy in object localization algorithm, while considering the unvarying light conditions.
机译:这项工作的主要目的是开发一种应用于自动机的物体识别和定位算法。该算法的开发分三个阶段进行:首先,对目标检测算法进行框架设计,从而为我们提供分段的目标矩阵。其次,对目标识别算法进行了框架化,最终给出了被识别目标的目标标签。第三,从物体定位算法中找出被识别物体的位置。视觉对于机器人在无定形环境中的功能至关重要。为了简化人与机器人之间的交互以及执行更复杂的操作,为了智能操作,将诸如视觉感知之类的认知能力附加到系统中。统一开发的算法将识别所需的对象,并给出其在世界坐标系中的位置。考虑到光照条件不变,本文开发的算法在目标检测和识别算法中达到了100%的精度,在目标定位算法中达到了98.03%至99.99%的精度,证明了它的快速性和良好性。

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