Quantcast

organized pointcloud vs. reducing number of points?

classic Classic list List threaded Threaded
1 message Options
Reply | Threaded
Open this post in threaded view
|  
Report Content as Inappropriate

organized pointcloud vs. reducing number of points?

PG1337
This post was updated on .
Hello,

i have a live pointcloud (no color) from kinect v2. this pointcloud is organized, but has a lot of nan values. which task is better for the following tool chain:

a) give up "organized" and remove all nan values. my thought: reducing the number of all points reduces the loop time for many following filter, etc.

b) keep the pointcloud "organized" and don't remove nan values. my thought: as mentionend in the tutorial here http://pointclouds.org/documentation/tutorials/basic_structures.php#basic-structures an organized pointcloud is lowering the costs for algorithms too.

which way is better? faster?

my overall task is real-time object recognition of an solid object, which geometry is well known.
greetings.
Loading...