Background Filtering and Object Detection With a Stationary LiDAR Using a Layer-Based Method
The connected vehicle environment is significant for the future road network. For constructing the connected vehicle environment, real-time data acquirement is always the prerequisite. Recently, using Light Detection and Ranging (LiDAR)-based roadside infrastructures are becoming a prevalent method...
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Veröffentlicht in: | IEEE access 2020, Vol.8, p.184426-184436 |
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description | The connected vehicle environment is significant for the future road network. For constructing the connected vehicle environment, real-time data acquirement is always the prerequisite. Recently, using Light Detection and Ranging (LiDAR)-based roadside infrastructures are becoming a prevalent method of obtaining real-time traffic data. However, the collected raw data from LiDAR cannot usually be used directly. The steps of data processing, like background filtering and object detection, are necessary. The processed data can then be employed in different applications. This paper proposed a novel layer-based searching method that is established with the help of the point distribution features to distinguish moving objects from the point cloud. It aimed to address the unexpected influence of factors such as congested situations and package loss. The new approach was also evaluated compared with the state-of-the-art methods by applying field data. The results showed that the proposed method is more effective than other methods. This method may be applicable to other types of rotating LiDAR for improving the background filtering performance. |
doi_str_mv | 10.1109/ACCESS.2020.3029341 |
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For constructing the connected vehicle environment, real-time data acquirement is always the prerequisite. Recently, using Light Detection and Ranging (LiDAR)-based roadside infrastructures are becoming a prevalent method of obtaining real-time traffic data. However, the collected raw data from LiDAR cannot usually be used directly. The steps of data processing, like background filtering and object detection, are necessary. The processed data can then be employed in different applications. This paper proposed a novel layer-based searching method that is established with the help of the point distribution features to distinguish moving objects from the point cloud. It aimed to address the unexpected influence of factors such as congested situations and package loss. The new approach was also evaluated compared with the state-of-the-art methods by applying field data. The results showed that the proposed method is more effective than other methods. 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For constructing the connected vehicle environment, real-time data acquirement is always the prerequisite. Recently, using Light Detection and Ranging (LiDAR)-based roadside infrastructures are becoming a prevalent method of obtaining real-time traffic data. However, the collected raw data from LiDAR cannot usually be used directly. The steps of data processing, like background filtering and object detection, are necessary. The processed data can then be employed in different applications. This paper proposed a novel layer-based searching method that is established with the help of the point distribution features to distinguish moving objects from the point cloud. It aimed to address the unexpected influence of factors such as congested situations and package loss. The new approach was also evaluated compared with the state-of-the-art methods by applying field data. The results showed that the proposed method is more effective than other methods. 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subjects | Background filtering Clustering algorithms Data processing Filtering Filtration Laser beams Laser radar layer-based method Lidar Object detection Object recognition Packet loss Real time Road construction Roadsides stationary LiDAR Traffic information Transportation networks |
title | Background Filtering and Object Detection With a Stationary LiDAR Using a Layer-Based Method |
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