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Improved Method for Object Recognition in Complex Scenes by Fusioning 3-D Information and RFID Technology

机译:一种融合3-D信息和RFID技术的复杂场景中物体识别的改进方法

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摘要

This work analyzes a new method for object recognition in complex scenes combining vision-based techniques applied to the 3-D data obtained using range sensors and object identification coming from radio frequency tags (radio frequency identification (RFID) technology). Three-dimensional vision-based algorithms for object recognition have many restrictions in practical applications, i.e., uncertainty, incapability for real-time tasks, etc., but they work well for pose determination once the object is recognized. On the other hand, RFID technology allows us to detect the presence of specific objects in a scene, but it cannot provide their localization, at least not with the accuracy required in applications such as ours. In this paper, we present a new and powerful recognition method obtained by fusing both techniques. The phases of the method are described, and abundant experimentation results are included. An in-depth performance analysis has been carried out to demonstrate the recognition improvements achieved by the algorithm when RFID assistance is considered. It helps to confirm the robustness of this fusion approach and prove its effectiveness. A final discussion is included, concerning what should be the most adequate size of the object database for optimal algorithm exploitation.
机译:这项工作分析了一种复杂场景中物体识别的新方法,该方法结合了基于视觉的技术,该技术应用于使用距离传感器获得的3-D数据和来自射频标签的物体识别(射频识别(RFID)技术)。基于三维视觉的对象识别算法在实际应用中有很多限制,即不确定性,实时任务的能力不足等,但是一旦识别出对象,它们就可以很好地用于姿态确定。另一方面,RFID技术使我们能够检测场景中特定对象的存在,但是它不能提供它们的定位,至少不能像我们这样的应用程序要求精确。在本文中,我们提出了一种通过融合两种技术而获得的强大的新识别方法。描述了该方法的各个阶段,并包括了丰富的实验结果。进行了深入的性能分析,以证明当考虑使用RFID辅助时该算法所实现的识别改进。它有助于确认这种融合方法的鲁棒性并证明其有效性。最后的讨论包括有关对象数据库最适合最佳算法开发的大小的讨论。

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