[shikhardevgupta]

Lidars are pretty powerful, but one big disadvantage of using point clouds for perception is that they are not colored. This makes identifying objects more difficult compared to camera images. However, by combining camera images with lidar data, we can enhance the point cloud by assigning colors to the points based on the corresponding camera image pixels. This makes visualizing and processing the point cloud much easier.

[PabloRobles]

Shameless plug, but I work on a multispectral lidar that does produce “colored” point clouds in the SWIR [0].

It is pretty cool, we use it for detection of humidity degree or for species discrimination (e.g. plants, minerals, chemicals…).

[0]: https://www.iridesense.tech/

[Groxx]

I'm not sure why you've just restated the first paragraph of the article.

[outofpaper]

Likely for the engagement... any bets as to if they are a bot or not?

[user_7832]

Their (human) reply makes me suspect it's a human using an llm without realizing how obvious it is that they're using one.

Edit: Just realized they're probably the author too of the post

[defrost]

Makes sense given English is likely not a strong primary language for them.

LLM's are getting heavy use from the ESL (and even English as a third or fourth language) crowd.

[polemic]

> one big disadvantage of using point clouds for perception is that they are not colored

That depends entirely on the capture device.

[shikhardevgupta]

True. But my reference point is Lidars which mostly produce non-colored points.