公开(公告)号：US11763564B1

公开(公告)日：2023-09-19

申请号：US17216147

申请日：2021-03-29

Applicant: Amazon Technologies, Inc.

Inventor： Najmeh Sadoughi Nourabadi ,  Kewen Chen ,  Tu Anh Ho ,  Christina Botkins ,  Dongqing Zhang ,  Muhammad Raffay Hamid

IPC: G06V20/40 ,  G06F16/71 ,  G06F16/75 ,  G06F16/735 ,  G06N20/00

CPC classification number: G06V20/46 ,  G06F16/71 ,  G06F16/735 ,  G06F16/75 ,  G06N20/00 ,  G06V20/41

Abstract: 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.

公开(公告)号：US12073625B1

公开(公告)日：2024-08-27

申请号：US18223487

申请日：2023-07-18

Applicant: Amazon Technologies, Inc.

Inventor： Najmeh Sadoughi Nourabadi ,  Kewen Chen ,  Tu Anh Ho ,  Christina Botkins ,  Dongqing Zhang ,  Muhammad Raffay Hamid

IPC: G06V20/40 ,  G06F16/71 ,  G06F16/735 ,  G06F16/75 ,  G06N20/00

CPC classification number: G06V20/46 ,  G06F16/71 ,  G06F16/735 ,  G06F16/75 ,  G06N20/00 ,  G06V20/41

Abstract: 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.

公开(公告)号：US11532111B1

公开(公告)日：2022-12-20

申请号：US17344690

申请日：2021-06-10

Applicant: Amazon Technologies, Inc.

Inventor： Dongqing Zhang ,  Muhammad Raffay Hamid ,  Xiaohan Nie ,  Shixing Chen

IPC: G06F17/00 ,  G06T11/60 ,  G11B27/031 ,  G10L15/26 ,  G06F40/134 ,  G06V20/40 ,  G06V40/16

Abstract: Techniques for a comic book feature are described herein. A visual data stream of a video may be parsed into a plurality of frames. Scene boundaries may be determined to generate a scene using the plurality of frames where a scene includes a subset of frames. A key frame may be determined for the scene using the subset of frames. An audio portion of an audio data stream of the video may be identified that maps to the subset of frames based on time information. The key frame may be converted to a comic image based on an algorithm. First dimensions and placement for a data object may be determined for the comic image. The data object may include the audio portion for the comic image. A comic panel may be generated for the comic image that incorporates the data object using the determined first dimensions and the placement.

公开(公告)号：US11748988B1

公开(公告)日：2023-09-05

申请号：US17236688

申请日：2021-04-21

Applicant: Amazon Technologies, Inc.

Inventor： Shixing Chen ,  Xiaohan Nie ,  David Jiatian Fan ,  Dongqing Zhang ,  Vimal Bhat ,  Muhammad Raffay Hamid

IPC: G06V20/40 ,  G06N20/00 ,  G06N5/04 ,  G06F16/73 ,  G06F16/78 ,  G11B27/34 ,  H04N5/14 ,  G11B27/036 ,  G06V10/75 ,  G06F18/22 ,  G06F18/214

CPC classification number: G06V20/46 ,  G06F16/73 ,  G06F16/78 ,  G06F18/214 ,  G06F18/22 ,  G06N5/04 ,  G06N20/00 ,  G06V10/751 ,  G06V20/49 ,  G11B27/036 ,  G11B27/34 ,  H04N5/147

Abstract: Techniques for automatic scene change detection in a video are described. As one example, a computer-implemented method includes extracting features of a query shot and its neighboring shots of a first set of shots without labels with a query model, determining a key shot of the neighboring shots which is most similar to the query shot based at least in part on the features of the query shot and its neighboring shots, extracting features of the key shot with a key model, training the query model into a trained query model based at least in part on a comparison of the features of the query shot and the features of the key shot, extracting features of a second set of shots with labels with the trained query model, and training a temporal model into a trained temporal model based at least in part on the features extracted from the second set of shots and the labels of the second set of shots.