Merged Point Cloud
Last updated
Last updated
The Merged Point Cloud feature allows users to see all the points over time (across all the frames of a batch) aggregated in the same coordinate system of the current frame resulting in one big point cloud. Therefore, ego motion data is mandatory for this type of scene.
It is used on sequential tasks to annotate stationary objects in a single .
By enabling the MPC, it's easy to detect and label all the stationary objects since they appear denser and brighter. While moving objects will leave a trail of points.
Improve Efficiency: By allowing all data points to be merged in a single frame, the user no longer has to traverse the sequence to find the ideal frame where the most points of the object are captured.
Static objects are also much clearly visible with the accumulated points
Improve Accuracy: By integrating data from multiple frames, merged point clouds can enhance the accuracy of object annotation. Annotators can use the combined data to make more informed decisions about the precise location of objects within the point cloud.
Toggle the MPC switch on the header of the annotation tool. This will aggregate and merge points across all the frames of the batch, by default on the next 20 frames.
The Multi Sensor Fusion tool supports various mechanisms of aggregating the point clouds across the sequence:
all
using frame jump length
Identify the stationary object (that is dense and bright)
Select the drawing tool and create the annotation on the object
If the annotation is a cuboid, it is propagated across all the frames.
If the object ceases to exist before the end of the frame, delete the annotation by right-clicking on it and selecting the delete option.
MPC has further options for merging points across a range of frames.
The tool provides multiple options
select a predefined option from the list
use the customizable start/end frame and hit enter
After triggering the merged point cloud, the timeline introduces a yellow to indicate the frames that are merged.
