LiDAR objects detection and classification using ML

we a project where were using Velodyne Lidar Puck-32,

The goal is to do vehicle detection and classifications (trucks, cars, motorcycles, others) in real-time via a trained classification model output (point cloud detected objects with bounding boxes, and type, speed of each object) only moving objects.

Thou output should be:
- Vehicles detected (identification)
- Classification (Trucks, Light Vehicles, Motor Cycles, Buses, .. etc.)

The candidate should be familiar with computer vision, Lidar, machine learning, DNN, and preferably writing code in Python.

This is the first step of a long-running project and a successful candidate will continue working on other tasks of similar nature in the future.

- Be able to classify vehicles in real-time
- Use of ML CNN or DNN

- Fully working software (preferably in Python) that classifies data from a sample .pcap file
- Source code
- Full documentation of the technical solution
About the recuiter
Member since Mar 14, 2020
Nellaisystems
from Rukwa, Tanzania

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