Systems and methods for detecting anomalies from data

摘要

The present disclosure concerns methods and/or systems for processing, detecting and/or notifying for the presence of anomalies or infrequent events from data. Some of the disclose methods and/or systems may be used on large-scale data sets. Certain applications are directed to analyzing sensor surveillance records to identify aberrant behavior. The sensor data may be from a number of sensor types including video and/or audio. Certain applications are directed to methods and/or systems that use compressive sensing. Certain applications may be performed in substantially real time.

主权项

1. A method for processing, detecting and/or notifying for the presence of at least one infrequent event from at least one large scale data set comprising:
receiving time series data; representing either the time series data, or one or more features of the time series data, as sets of vectors, matrices and/or tensors; performing compressive sensing on at least one vector, matrix and/or tensor set; decomposing the at least one compressive sensed vector, matrix and/or tensor set to extract a residual subspace; and identifying, using a computing device, potential infrequent events by analysing compressive sensed data projected into the residual subspace.