Abstract: A process reduces false positive security alerts. The process is performed at a computing device having one or more processors, and memory storing one or more programs configured for execution by the one or more processors. The process computes a depth map for a scene monitored by a video camera using a plurality of IR images captured by the video camera and uses the depth map to identify a first region within the scene having historically above average false positive detected motion events. In some instances, the first region is a ceiling, a window, or a television. The process monitors a video stream provided by the video camera to identify motion events, excluding the first region, and generates a motion alert when there is detected motion in the scene outside of the first region and the detected motion satisfies threshold criteria.

Abstract: A process reduces false positive security alerts. The process is performed at a computing device having one or more processors, and memory storing one or more programs configured for execution by the one or more processors. The process computes a depth map for a scene monitored by a video camera using a plurality of IR images captured by the video camera and uses the depth map to identify a first region within the scene having historically above average false positive detected motion events. In some instances, the first region is a ceiling, a window, or a television. The process monitors a video stream provided by the video camera to identify motion events, excluding the first region, and generates a motion alert when there is detected motion in the scene outside of the first region and the detected motion satisfies threshold criteria.

Abstract: The various embodiments described herein include methods, devices, and systems for categorizing motion event candidates. In one aspect, a method includes receiving and processing video frames that include a motion event candidate. The processing includes: (a) obtaining background factors corresponding to a background in at least a subset of the video frames; (b) utilizing the background factors to identify one or more motion entities; (c) for each motion entity, obtaining one or more representative motion vectors based on a motion track of the respective motion entity; (d) identifying one or more features in at least a subset of the video frames; and (e) aggregating the background factors, the representative motion vectors, and the features to generate motion features. The method further includes sending the motion features to an event categorizer, where the event categorizer assigns a motion event category to the motion event candidate based on the received motion features.

Abstract: A business logic server for forming priority data structures includes a memory and a processing module. The processing module communicatively coupled to the memory. The processing module receives at least one transmission rule and a data download and stores the at least one transmission rule and the data download in the memory. The processing module is programmed to format the at least one transmission rule into at least one priority data structure and stores the priority data structure in the memory. The processing module is programmed to create an input file in the memory and format the data download into the input file. The processing module transmits the input file and the at least one priority data structure from the memory to a network logic server.