For example, a 10 second segment is generated every second, such that a new segment overlaps the prior segment by 9 seconds. In some implementations, after the event processor module obtains the video portion corresponding to an event candidate, the event processor module 3146 obtains background factors and performs motion entity detection identification, motion vector generation for each motion entity, and feature identification. Once the event processor module 3146 completes these tasks, the event categorizer module 3148 aggregates all of the information and generates a categorization for the motion event candidate. In some implementations, false positive suppression is optionally performed to reject some motion event candidates before the motion event candidates are submitted for event categorization. In some implementations, determining whether a motion event candidate is a false positive includes determining whether the motion event candidate occurred in a particular zone. In some implementations, determining whether a motion event candidate is a false positive includes analyzing an importance score for the motion event candidate. The importance score for a motion event candidate is optionally based on zones of interest involved with the motion event candidate, background features, motion vectors, scene features, entity features, motion features, motion tracks, and the like. FIG. 6 is a block diagram illustrating a representative client device 220 associated with a user account in accordance with some implementations. The client device 220, typically, includes one or more processing units CPUs 602, one or more network interfaces 604, memory 606, and one or more communication buses 608 for interconnecting these components sometimes called a chipset. Optionally, the client device also includes a user interface 610 and one or more built in sensors 690 e.