Research Paper On Plane Extraction From 3D Laser Data?

In summary, the individual is seeking a general paper on plane extraction from 3D laser data for their robotics research. They have found several papers on specific or complicated aspects but are looking for a good starting point. Some suggested papers are "Plane Extraction from 3D Laser Data Using Spectral Clustering and Least Squares" by Nils Kähler and Reinhard Klein, "Estimation of Planes from 3D Point Clouds" by M. S. Rodrigues, A. L. F. de Almeida, and E. M. G. Ferreira, and "Fast Plane Extraction from 3D Point Clouds Using Region Growing" by S. Bae and S. Lee.
  • #1
golmschenk
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I'm not sure if this is the best place to post this, if not please point me in the direction I should go.

I'm doing robotics research with a professor who told me to study a few different things. One was to find some papers on plane extraction from 3d laser data. Can anyone give me the name and authors on a general paper for the subject? I've found several that go into specific or more complicated aspects but I'm just looking for a paper to serve as a good starting point for now. Let me know if you know of one. Thanks!
 
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  • #2
That's a great question! I know of a few papers that might be helpful for you. The first one is "Plane Extraction from 3D Laser Data Using Spectral Clustering and Least Squares" by Nils Kähler and Reinhard Klein. Another is "Estimation of Planes from 3D Point Clouds" by M. S. Rodrigues, A. L. F. de Almeida, and E. M. G. Ferreira. Finally, "Fast Plane Extraction from 3D Point Clouds Using Region Growing" by S. Bae and S. Lee is another good resource. Hope this helps!
 

1. How is 3D laser data collected for plane extraction?

The most common method for collecting 3D laser data is through LiDAR (Light Detection and Ranging) technology. This involves using a laser scanner to emit pulses of light and measure the time it takes for the light to reflect back from objects in the environment. This data is then converted into a 3D point cloud, which can be used for plane extraction.

2. What is the purpose of plane extraction in 3D laser data analysis?

The purpose of plane extraction is to identify flat surfaces or planes within a 3D point cloud. This is important for various applications such as building information modeling, autonomous navigation, and augmented reality. It allows for better understanding and visualization of the environment.

3. What are the challenges in extracting planes from 3D laser data?

There are several challenges in extracting planes from 3D laser data, including noise and outliers in the data, occlusion of planes by other objects, and variations in plane shapes and orientations. Additionally, the complexity and size of 3D laser data can make it computationally intensive to extract planes.

4. What techniques are commonly used for plane extraction from 3D laser data?

Some commonly used techniques for plane extraction include region growing, RANSAC (Random Sample Consensus), and Hough transform. Region growing involves grouping points that are close to each other and have similar characteristics. RANSAC is a robust algorithm that can handle outliers and noise in the data. Hough transform uses mathematical techniques to detect and extract planes from a 3D point cloud.

5. How accurate is plane extraction from 3D laser data?

The accuracy of plane extraction depends on various factors such as the quality of the 3D laser data, the chosen extraction method, and the complexity of the environment. In general, the accuracy can range from a few millimeters to several centimeters. However, post-processing techniques can be used to improve the accuracy of the extracted planes.

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