Summary of 3d Object Detection and High-resolution Traffic Parameters Extraction Using Low-resolution Lidar Data, by Linlin Zhang et al.
3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data
by Linlin Zhang, Xiang Yu, Armstrong Aboah, Yaw Adu-Gyamfi
First submitted to arxiv on: 13 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper addresses the limitations of using Light Detection and Ranging (LiDAR) for traffic volume data collection. Traditional manual methods are time-consuming and costly, while LiDAR offers efficient and accurate data collection. The proposed framework employs a single LiDAR system to reduce costs and addresses the limitation of missing point cloud information by developing a Point Cloud Completion (PCC) framework. Additionally, zero-shot learning techniques are used for vehicle and pedestrian detection, and a unique framework is proposed for extracting low-to-high features from objects of interest. The study demonstrates automatic 3D bounding box generation without human intervention using 2D bounding box detection and extracted height information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes it easier to collect important traffic data. Right now, people have to spend a lot of time collecting this data by hand, which is expensive and slow. The study uses advanced technology called LiDAR to make the process faster and more accurate. They found ways to make LiDAR work better by using just one device instead of multiple ones, and they developed a way to automatically add missing information. This makes it easier for people to collect traffic data without having to do it all by hand. |
Keywords
* Artificial intelligence * Bounding box * Zero shot
