Quick 3D Point Cloud Labelling Process #3D #pointcloud #labelling

Due to YouTube's recent changes on high resolution playback, it is sadly impossible to play high-resolution video with audio without client-side JavaScript enabled. Switch to SD quality or enable JavaScript to play your video with audio.

High Definition Standard Definition

Stats For Nerds

Theater

Video id : EdnMo9kktpw
ImmersiveAmbientModecolor: #cb9b96 (color 2)
Video Format : (720p) openh264 ( https://github.com/cisco/openh264) mp4a.40.2 | 44100Hz
Audio Format: 140 ( High )
PokeEncryptID: d20699fb98a31e63c0931ce92d91b4dd6f9018cd53389b9224f3bbd218fa8db2ca918c5203f4b1ad9e1933136153460f
Proxy : cal1.iv.ggtyler.dev - refresh the page to change the proxy location
Date : 1733019636395 - unknown on Apple WebKit
Mystery text : RWRuTW85a2t0cHcgaSAgbG92ICB1IGNhbDEuaXYuZ2d0eWxlci5kZXY=
143 : true

Quick 3D Point Cloud Labelling Process #3D #pointcloud #labelling

Jump to Connections

Florent Poux

4.98K Subs

Download

Redirect!

8 Views • Dec 20, 2023 • Click to toggle off description

When labeling a 3D point cloud, the process typically begins with importing the data into a software program that allows for manual or automatic labeling. If using manual labeling, the user will typically be presented with an interface that allows them to select and label individual or groups of points based on their characteristics, such as color, shape, or location within the point cloud. Automatic labeling can also be utilized, typically through the use of machine learning algorithms, to identify and label objects or features within the point cloud.

Once all points have been labeled, the data can be exported into a format that is usable for further analysis or application. It's important to ensure accuracy and consistency throughout the labeling process to ensure the best results.

Metadata And Engagement

Views : 8
Genre: Science & Technology
Uploaded At Dec 20, 2023 ^^

warning: returnyoutubedislikes may not be accurate, this is just an estiment ehe :3
Rating : 1 (1/0 LTDR)

0.00% of the users lieked the video!!
100.00% of the users dislieked the video!!
User score: -50.00- Overwhelmingly Negative

RYD date created : 2023-12-20T23:27:26.560777Z
See in json

0 Comments