Trajectory cluster model for learning trajectory patterns in video data
US12051210B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 25, 2021 |
| Grant date | Jul 30, 2024 |
| Priority date | — |
| Expiry date | Oct 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG08B13/19613
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.