Nvidia Corporation

Somayyeh Rahimi

Ruthie D Lyle

Pratyush Mahapatra

Systems and methods of compressing video content as encoded data and selectively reconstructing portions of the content are disclosed. The proposed systems provide a computer-implemented process configured to classify a person's behavior(s) during a video and encode the behaviors as a representation of the video. When playback of the video is requested, a video navigation assistant will allow the end-user to select specific segments of the video based on topics discussed in the video and the codes that were generated to represent the video. The user is then able to move through segments of the video in a sequence that aligns with their viewing preferences.

Conversational AI-encoded language for video navigation

Systems and methods of compressing video data are disclosed. The proposed systems provide a computer-implemented process configured to classify a person's behavior(s) during a video and encode the behaviors as a representation of the video. When playback of the video is requested, a reconstruction of the video is generated by a video synthesizer based on a reference image of the person and the sequence of codes corresponding to their behavior during the video. Storage and transmission of the video can then be limited to the reference image and the behavioral codes rather than the video file itself, significantly reducing memory and bandwidth requirements.

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Del Mar, CA, United States of America

Somayyeh Rahimi