Kinect in neurorehabilitation: Computer vision system for real time hand and object detection and distance estimation

Matija Štrbac, Marko Marković, D. Popović
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引用次数: 23

Abstract

This paper presents image processing and scene analysis methods that can provide artificial vision that is of interest for automatic selection of hand trajectory and prehension. The new algorithm, which uses data from the Kinect sensor, allows real-time detection of the hand of the person grasping an object at working table in front of that person. The outputs are real world coordinates of the hand and the object. The image processing is done in Matlab over the depth image stream taken from the Microsoft Kinect as a sensory input. Results show that in the presented system setup our program is capable of tracking hand movements in the transverse plane and estimating hand and object position in real-time with tolerable estimation error for the selection of stimulation paradigm that could control hand trajectory.
神经康复中的Kinect:用于实时手和物体检测和距离估计的计算机视觉系统
本文提出了图像处理和场景分析方法,这些方法可以为手部轨迹的自动选择和抓取提供人工视觉。新算法使用来自Kinect传感器的数据,可以实时检测到人们在工作台上抓住物体的手。输出是手和物体的真实世界坐标。图像处理是在Matlab中通过从微软Kinect作为感官输入的深度图像流完成的。结果表明,在该系统设置下,我们的程序能够在可容忍的估计误差范围内实时跟踪手部横向运动并估计手部和物体的位置,从而选择能够控制手部运动轨迹的刺激模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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