The Boeing Company

Yuri Levchuk

Zachary D Jorgensen

Jan Wei Pan

Hieu Tat Nguyen

An apparatus is provided for automated object tracking in a video feed. The apparatus receives and sequentially processes a plurality of frames of the video feed to track objects. In particular, a plurality of objects in a frame are detected and assigned to a respective track fragment. A kinematic, visual, temporal or machine learning-based feature of an object is then identified and stored in metadata associated with the track fragment. A track fragment for the object is identified in earlier frames based on a comparison of the feature and a corresponding feature in metadata associated with the earlier frames. The track fragments for the object in the frame and the object in the earlier frames are linked to form a track of the object. The apparatus then outputs the video feed with the track of the object as an overlay thereon.

Automated object tracking in a video feed using machine learning

An apparatus is provided for automated object and activity tracking in a live video feed. The apparatus receives and processes a live video feed to identify a plurality of objects and activities therein. The apparatus also generates natural language text that describes a storyline of the live video feed using the plurality of objects and activities so identified. The live video feed is processed using computer vision, natural language processing and machine learning, and a catalog of identifiable objects and activities. The apparatus then outputs the natural language text audibly or visually with a display of the live video feed.

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Potomac, MD, United States of America

Yuri Levchuk