US 2017/0286781 A1 · TRAJECTORY CLUSTER MODEL FOR LEARNING TRAJECTORY PATTERNS IN VIDEOS DATA

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.

Claims20

Dependent claims

A computer-implemented method for analyzing trajectories of objects in a scene depicted in video frames captured by a video camera, comprising:

determining, based on a first distance between a received trajectory and a stored trajectory cluster, whether the received trajectory maps to the stored trajectory cluster;
and
if the received trajectory maps to the stored trajectory cluster:
determining a first score based on at least a first cumulative probability distribution indicating probability of the received trajectory being at least the first distance from the stored trajectory cluster, and
issuing an alert if the first score exceeds a threshold.

2 more elements

A non-transitory computer-readable storage medium storing instructions, which when executed by a computer system, perform operations for analyzing trajectories of objects in a scene depicted in video frames captured by a video camera, the operations comprising:

determining, based on a first distance between a received trajectory and a stored trajectory cluster, whether the received trajectory maps to the stored trajectory cluster;
and
if the received trajectory maps to the stored trajectory cluster:
determining a first score based on at least a first cumulative probability distribution indicating probability of the received trajectory being at least the first distance from the stored trajectory cluster, and
issuing an alert if the first score exceeds a threshold.

2 more elements

Dependencies are inferred from the claim text.

Trajectory cluster model for learning trajectory patterns in videos data

Life of this patent

Trajectory cluster model for learning trajectory patterns in videos data

Life of this patent

Abstract

Claims20