multimedialabsfu/learned-point-cloud-compression-for-classification
[MMSP 2023, PCS 2024]
This project offers a specialized way to send 3D point cloud data from devices like sensors or mobile phones to a central server for analysis. It takes raw 3D point cloud scans as input and outputs a compressed version that's optimized for classification tasks on the server, ensuring faster and more efficient processing. This tool is for engineers or researchers working with edge devices that need to perform machine vision tasks like classifying objects in 3D environments but have limited computational power.
No commits in the last 6 months.
Use this if you need to perform machine vision classification on 3D point cloud data captured by resource-constrained edge devices and send it to a server for processing efficiently.
Not ideal if your primary goal is perfect reconstruction of the 3D point cloud data rather than optimizing for classification accuracy and speed.
Stars
20
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 22, 2024
Commits (30d)
0
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