公开(公告)号：US20250131706A1

公开(公告)日：2025-04-24

申请号：US19001315

申请日：2024-12-24

Applicant: Palantir Technologies Inc.

Inventor： Leah ANDERSON ,  Mark Montoya ,  Andrew Elder ,  Alisa Le ,  Ezra Zigmond ,  Jocelyn Rivero

IPC: G06V10/94 ,  G06F18/21 ,  G06F18/214 ,  G06V10/774 ,  G06V20/52

Abstract: 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.

公开(公告)号：US20230368519A1

公开(公告)日：2023-11-16

申请号：US18226141

申请日：2023-07-25

Applicant: Palantir Technologies Inc.

Inventor： Leah ANDERSON ,  Mark MONTOYA ,  Andrew ELDER ,  Alisa LE ,  Ezra ZIGMOND ,  Jocelyn RIVERO

IPC: G06V10/94 ,  G06V10/774 ,  G06V20/52

CPC classification number: G06V10/945 ,  G06V10/774 ,  G06F18/213 ,  G06F18/2148 ,  G06V20/53 ,  G06F18/2178

Abstract: 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.