Understand the 3D point cloud object tracking task type

Use this task type when you want workers to add and fit 3D cuboids around objects to track their movement across 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.

For this task type, the data object that workers label is a sequence of point cloud frames. A sequence is defined as a temporal series of point cloud frames. Ground Truth renders a series of 3D point cloud visualizations using a sequence you provide and workers can switch between these 3D point cloud frames in the worker task interface.

Ground Truth provides workers with tools to annotate objects with 9 degrees of freedom (x,y,z,rx,ry,rz,l,w,h) in three dimensions in both 3D scene and projected side views (top, side, and back). When a worker draws a cuboid around an object, that cuboid is given a unique ID, for example Car:1 for one car in the sequence and Car:2 for another. Workers use that ID to label the same object in multiple frames.

You can also provide camera data to give workers more visual information about scenes in the frame, and to help workers draw 3D cuboids around objects. When a worker adds a 3D cuboid to identify an object in either the 2D image or the 3D point cloud, and the cuboid shows up in the other view.

You can adjust annotations created in a 3D point cloud object detection labeling job using the 3D point cloud object tracking adjustment task type.

If you are a new user of the Ground Truth 3D point cloud labeling modality, we recommend you review 3D point cloud labeling jobs overview. This labeling modality is different from other Ground Truth task types, and this page provides an overview of important details you should be aware of when creating a 3D point cloud labeling job.

The following topics explain how to create a 3D point cloud object tracking job, show what the worker task interface looks like (what workers see when they work on this task), and provide an overview of the output data you get when workers complete their tasks. The final topic provides useful information for creating object tracking adjustment or verification labeling jobs.