Object Tracking with Frame Level-Labeling

Audrey Boguchwal

April 2, 2020

2 Minute Read

We live in an ever-changing world, where AI-enabled technology has become a new normal for society. To assist top organizations in their efforts to build smarter computer vision algorithms, we’ve rolled out a new release for video and 3D object-tracking in our leading data annotation platform.

There are a number of applications that use computer vision to track how the world, and the objects in it, change overtime. For a self-driving car to navigate safely, it needs to track other moving objects on the road and make predictions about their future movement, so it can plan its driving path.

AR and VR applications like video games need to track the motion of individual people to create a seamless digital experience. These vision applications have something in common: they all seek to understand the change in position, behavior and characteristics of unique objects over time. 

Object tracking annotation offers object tracking capabilities for complex scenarios, including path planning, traffic light status, sentiment analysis, etc.

This frame-level labeling technology allows unique objects to be dynamically tracked across a video or a sequence of 3D point cloud data from a Lidar sensor. Change in position and pose are captured with annotation shapes like cuboids, polygons and bounding boxes.

Sama supports custom label taxonomies for both the main object class (person, car, etc.) and dynamic labeling for other object characteristics that change over time, such as visibility percentage of an object or a specific set of characteristics like emotions. Sama’s built-in automated interpolation between video frames helps ensure efficient, high quality labeled training data for a variety of object tracking use cases.

For over 10 years, Sama has delivered turnkey, high-quality training data and validation to train the world's leading AI technologies. Video and 3D object tracking are no exception, and this update for video object tracking annotation in 2D RGB video and 3D Lidar data will continue to assist organizations in quickly building models that better reflect real-world behavior.

Sama has deep expertise working with training data for object tracking use cases across a variety of industries including autonomous vehicles, AR/VR, retail and e-commerce, communications, media and entertainment, to name just a few.

Download our solution brief to learn more about our secure training data annotation platform, or contact our team here.