Various modes of transportation traverse our roadways, highlighting the importance of object classification for improving traffic safety. Optical sensors that rely on visual data encounter challenges in adverse weather conditions, where poor visibility hinders target classification. In this project we use an off-the-shelf millimeter wave Frequency Modulated Continuous Wave (FMCW) radar -- Texas Instruments IWR1843BOOST module to classify on road objects. By combining the radar module, Robot Operating System (ROS), and Python scripts, we extracted a dataset of 3D point cloud images.

Dataset Files

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[1] Pranjal Mahajan, "Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/qjhv-g740. Accessed: Jun. 14, 2024.
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doi = {10.21227/qjhv-g740},
url = {http://dx.doi.org/10.21227/qjhv-g740},
author = {Pranjal Mahajan },
publisher = {IEEE Dataport},
title = {Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians},
year = {2024} }
TY - DATA
T1 - Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians
AU - Pranjal Mahajan
PY - 2024
PB - IEEE Dataport
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Pranjal Mahajan. (2024). Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians. IEEE Dataport. http://dx.doi.org/10.21227/qjhv-g740
Pranjal Mahajan, 2024. Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians. Available at: http://dx.doi.org/10.21227/qjhv-g740.
Pranjal Mahajan. (2024). "Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians." Web.
1. Pranjal Mahajan. Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/qjhv-g740
Pranjal Mahajan. "Top-View Noise-Filtered Point Cloud of 2-wheelers, 4-wheelers and Pedestrians." doi: 10.21227/qjhv-g740