Abstract: A method that determines whether a detected event is a significant event requiring action in a video surveillance system. Determined event attributes and object attributes are analyzed to determine if the potential event should trigger an action by the surveillance system. If the potential event should trigger an action, at least one action is triggered. Actions may include relevant event attribute and object attribute information. Potential event may include events detected by a sensor, or external events communicated by an external system to the surveillance system. Event attributes may include location and type of the potential event. Object attributes may include an identification of an object, and attributes associated with the identified object. If an object cannot be positively identified, object attributes may include potential object identifications or determined group associations of the object.

Abstract: A pipeline architecture for analyzing multiple streams of video is embodied, in part, in a layer of application program interfaces (APIs) to each stage of processing. Buffer queuing is used between some stages, which helps moderate the load on the CPU(s). Through the layer of APIs, innumerable video analysis applications can access and analyze video data flowing through the pipeline, and can annotate portions of the video data (e.g., frames and groups of frames), based on the analyses performed, with information that describes the frame or group. These annotated frames and groups flow through the pipeline to subsequent stages of processing, at which increasingly complex analyses can be performed. At each stage, portions of the video data that are of little or no interest are removed from the video data. Ultimately, “events” are constructed and stored in a database, from which cross-event and historical analyses may be performed and associations with, and among, events may be made.