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公开(公告)号：US20210097349A1
公开(公告)日：2021-04-01
申请号：US16679092
申请日：2019-11-08
发明人： Leah Anderson , Mark Montoya , Andrew Elder , Alisa Le , Ezra Zigmond , Jocelyn Rivero
摘要： Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
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公开(公告)号：US20220067448A1
公开(公告)日：2022-03-03
申请号：US17522470
申请日：2021-11-09
发明人： Leah Anderson , Mark Montoya , Andrew Elder , Alisa Le , Ezra Zigmond , Jocelyn Rivero
摘要： Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
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公开(公告)号：US11710305B2
公开(公告)日：2023-07-25
申请号：US17522470
申请日：2021-11-09
发明人： Leah Anderson , Mark Montoya , Andrew Elder , Alisa Le , Ezra Zigmond , Jocelyn Rivero
IPC分类号： G06K9/62 , G06K9/00 , G06V10/94 , G06V20/52 , G06F18/21 , G06F18/213 , G06F18/214 , G06V10/774
CPC分类号： G06V10/945 , G06F18/213 , G06F18/2148 , G06F18/2178 , G06V10/774 , G06V20/53
摘要： Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
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公开(公告)号：US11170268B2
公开(公告)日：2021-11-09
申请号：US16679092
申请日：2019-11-08
发明人： Leah Anderson , Mark Montoya , Andrew Elder , Alisa Le , Ezra Zigmond , Jocelyn Rivero
摘要： Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
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