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http://dx.doi.org/10.5909/JBE.2020.25.5.808

Noise Reduction Method Using Randomized Unscented Kalman Filter for RGB+D Camera Sensors  

Kwon, Oh-Seol (School of Electronical Electronics and Control Engineering, Changwon National University)
Publication Information
Journal of Broadcast Engineering / v.25, no.5, 2020 , pp. 808-811 More about this Journal
Abstract
This paper proposes a method to minimize the error of the Kinect camera sensor by using a random undirected Kalman filter. Kinect cameras, which provide RGB values and depth information, cause nonlinear errors in the sensor, causing problems in various applications such as skeleton detection. Conventional methods have tried to remove errors by using various filtering techniques. However, there is a limit to removing nonlinear noise effectively. Therefore, in this paper, a randomized unscented Kalman filter was applied to predict and update the nonlinear noise characteristics, we next tried to enhance a performance of skeleton detection. The experimental results confirmed that the proposed method is superior to the conventional method in quantitative results and reconstructed images on 3D space.
Keywords
Kinetic camera; RUKF; and skeleton detection;
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