Amazon Technologies, Inc.

Kewen Chen

Muhammad Raffay Hamid

Tu Anh Ho

Najmeh Sadoughi Nourabadi

Christina Botkins

Shixing Chen

Maciej Tadeusz Golonka

Dongqing Zhang

Arun Velayudhan Pillai

Anantha Krishna Hodrali Srinivasa Bhatta

Jacob William Jensen

Anne TuAnh Thanh Thuy Ho

Zuzanna Maria Stepniakowska Coggins

Guy Friedel

Dhaval Damani

Systems and methods are provided herein for generating optimized video segments. A derivative video segment (e.g., a scene) can be identified from derivative video content (e.g., a movie trailer). The segment may be used a query to search video content (e.g., the movie) for the segment. Once found, an optimized video segment may be generated from the video content. The optimized video segment may have a different start time and/or end time than those corresponding to the original segment. Once optimized, the video segment may be presented to a user or stored for subsequent content recommendations.

Techniques for generating optimized video segments utilizing a visual search

Methods and apparatus are described for generating compelling preview clips of media presentations. Compelling clips are identified based on weighted combinations of attribute scores determined for indices of a media presentation. One or more of these compelling clips are then provided to a client device for playback.

Identifying compelling scenes at scale by mapping characteristics

Methods and apparatus are described for generating compelling preview clips of media presentations. Compelling clips are identified based on the extent to which human faces are shown and/or the loudness of the audio associated with the clips. One or more of these compelling clips are then provided to a client device for playback.

Leveraging computer vision and machine learning to identify compelling scenes

Systems, methods, and computer-readable media are disclosed for systems and methods for automated video preview generation. Example methods may include determining video content, determining a first shot transition, a second shot transition, a third shot transition, and a fourth shot transition in the video content, and determining that human speech is present during the first shot transition and the second shot transition. Example methods may include determining a first timestamp associated with the third shot transition, determining a second timestamp associated with the fourth shot transition, generating a first video preview of the video content, where the first video preview includes a segment of the video content from the first timestamp to the second timestamp, and causing presentation of the first video preview, where the first video preview does not include a segment of the video content between the first shot transition and the second shot transition.

Automated video preview generation

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Bellevue, WA, United States of America

Kewen Chen