- 专利标题: Trajectory cluster model for learning trajectory patterns in video data
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申请号: US17509837申请日: 2021-10-25
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公开(公告)号: US12051210B2公开(公告)日: 2024-07-30
- 发明人: Gang Xu , Ming-Jung Seow , Tao Yang , Wesley Kenneth Cobb
- 申请人: Intellective Ai, Inc.
- 申请人地址: US TX Dallas
- 专利权人: Intellective Ai, Inc.
- 当前专利权人: Intellective Ai, Inc.
- 当前专利权人地址: US TX Dallas
- 代理机构: COOLEY LLP
- 主分类号: G06K9/00
- IPC分类号: G06K9/00 ; G06N20/00 ; G06T7/20 ; G06V10/75 ; G06V20/52 ; G06V10/62 ; G06V20/40 ; G08B13/196
摘要:
Techniques are disclosed for analyzing and learning behavior in an acquired stream of video frames. In one embodiment, a trajectory analyzer clusters trajectories of objects depicted in video frames and builds a trajectory model including the trajectory clusters, a prior probability of assigning a trajectory to each cluster, and an intra-cluster probability distribution indicating the probability that a trajectory mapping to each cluster is least various distances away from the cluster. Given a new trajectory, a score indicating how unusual the trajectory is may be computed based on the product of the probability of the trajectory mapping to a particular cluster and the intra-cluster probability of the trajectory being a computed distance from the cluster. The distance used to match the trajectory to the cluster and determine intra-cluster probability is computed using a parallel Needleman-Wunsch algorithm, with cells in antidiagonals of a matrix and connected sub-matrices being computed in parallel.
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