Abstract: A video analytics system includes a first database for storing searchable time-stamped transactional data indicative of activity within a monitored system, a second database for storing time-stamped video metadata, wherein the time-stamped video metadata comprises searchable attributes associated with a raw video data stream; and a rule-based correlation server for comparing the time-stamped transactional data with the time-stamped video metadata to identify correlation events indicating potential activity of interest. An output subsystem reports the correlation events from the correlation engine. The analytics system is useful for detecting fraud in ATM transactions by comparing the transactional data, for example, the presence of a transaction, with video metadata, for example, indicating whether a transaction occurs when a person is present, for how long the person is there.

Abstract: A video analytics system includes a first database for storing searchable time-stamped transactional data indicative of activity within a monitored system, a second database for storing time-stamped video metadata, wherein the time-stamped video metadata comprises searchable attributes associated with a raw video data stream; and a rule-based correlation server for comparing the time-stamped transactional data with the time-stamped video metadata to identify correlation events indicating potential activity of interest. An output subsystem reports the correlation events from the correlation engine. The analytics system is useful for detecting fraud in ATM transactions by comparing the transactional data, for example, the presence of a transaction, with video metadata, for example, indicating whether a transaction occurs when a person is present, for how long the person is there.

Abstract: A video analytics system includes a first database for storing searchable time-stamped transactional data indicative of activity within a monitored system, a second database for storing time-stamped video metadata, wherein the time-stamped video metadata comprises searchable attributes associated with a raw video data stream; and a rule-based correlation server for comparing the time-stamped transactional data with the time-stamped video metadata to identify correlation events indicating potential activity of interest. An output subsystem reports the correlation events from the correlation engine. The analytics system is useful for detecting fraud in ATM transactions by comparing the transactional data, for example, the presence of a transaction, with video metadata, for example, indicating whether a transaction occurs when a person is present, for how long the person is there.

Abstract: An analytics server for use in a transaction system with a terminal for performing authenticated user-initiated transactions and generating transaction data including a user identity associated with each transaction and a camera for capturing image data of a user performing an authenticated transaction at the terminal is configured to extract user characteristic features from the image data associated with authenticated transactions and iteratively update a user database of the user characteristic features over multiple authenticated transactions. The analytics server is further configured to compute a match score, based on preset rules, of the user characteristic features for a current transaction with the user characteristic features associated with a current user stored in the user database, and raise an alarm when the match score fails to meet a threshold value.