Title | ||
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Real-Time Removing Of Outliers And Noise In 3d Point Clouds Applied In Robotic Applications |
Abstract | ||
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Nowadays, robots are able to carry out a complex series of actions, to take decisions, to interact with their environment and generally to perform plausible reactions. Robots' visual ability plays an important role to their behavior, helping them to efficiently manage the received information. In this paper, we present a real time method for removing outliers and noise of 3D point clouds which are captured by the optical system of robots having depth camera at their disposal. Using our method, the final result of the created 3D object is smoothed providing an ideal form for using it in further processing techniques; namely navigation, object recognition and segmentation. In our experiments, we investigate real scenarios where the robot moves while it acquires the point cloud in natural light environment, so that unpleasant noise and outliers become apparent. |
Year | DOI | Venue |
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2017 | 10.1007/978-3-319-66471-2_2 | INTERACTIVE COLLABORATIVE ROBOTICS (ICR 2017) |
Keywords | Field | DocType |
Robotic vision, 3D point clouds denoising, Outliers removing | Computer vision,Segmentation,Outlier,Artificial intelligence,Point cloud,Robot,Cognitive neuroscience of visual object recognition,Physics | Conference |
Volume | ISSN | Citations |
10459 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Gerasimos Arvanitis | 1 | 9 | 6.21 |
Aris S. Lalos | 2 | 192 | 32.84 |
K. Moustakas | 3 | 285 | 58.02 |
Nikos Fakotakis | 4 | 860 | 117.68 |