Annotating the Movement of People in Videos Using Keypoints
Client Profile
Industry: Technology services
Location: USA
Size: 10-50
Company Bio
The client has a suite of products that help companies create and manage the huge amounts of customized datasets they need to build algorithms. They use AI to make customized AI training data for large tech companies to help their clients develop machine learning-based features in their products multiple times faster than they could themselves.
Overview
Marking the human skeleton with key points on each frame in a video.
Business Challenge
The client needed to annotate the human skeleton with key points on each frame in a video which is very challenging because the person is constantly moving in the video and therefore the combinations of points are constantly changing. Moreover, the people in the video can be in various positions i.e. vertical (running, jumping, squatting), horizontal (push-ups, laying down, plank position). Moreover, the algorithm evaluates key points differently when a person is in different positions.
Solutions Provided by Mindy Support
Mindy Support assembled a team of 115 full-time data annotators to perform all of the needed labeling tasks. In total we annotated 12,000 videos which is 1,200,000 frames. All of this work was done within the specified time frame of 60 days and the quality score was >95%.
Results Delivered to the Client
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We have a minimum threshold for starting any new project, which is 735 productive man-hours a month (equivalent to 5 graphic annotators working on the task monthly).
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