The disclosed embodiments include an electronic device with a display, processor(s), and memory. The electronic device displays a user interface on the display, the user interface including video information corresponding to a camera, the video information including a field of view of the camera. The electronic device receives user identification of a spatial zone within the user interface, the spatial zone corresponding to at least a portion of the field of view of the camera; and forgoes user notification of subsequent motion events involving the spatial zone.

Video tracking systems and methods include a peripheral master tracking process integrated with one or more tunnel tracking processes. The video tracking systems and methods utilize video data to detect and/or track separately several stationary or moving objects in a manner of tunnel vision. The video tracking system includes a master peripheral tracker for monitoring a scene and detecting an object, and a first tunnel tracker initiated by the master peripheral tracker, wherein the first tunnel tracker is dedicated to track one detected object.

The techniques described herein relate to computerized methods, systems and non-transitory computer-readable media for determining a plurality of regions of interest from an image of a scene for motion detection. The methods can include generating the regions of interest using image segmentation techniques and receiving user selection to designate one or more regions as motion detection zones. The methods can also automatically recommend motion detection zones. The methods can include subsequently capturing one or more images of a scene and performing motion detection in the one or more images of the scene using the designated motion detection zones.

A system for monitoring shopping baskets (e.g., baskets on human-propelled carts, motorized carts, or hand-carried baskets) can include a computer vision unit that can image a surveillance region (e.g., an exit to a store), determine whether a basket is empty or loaded with merchandise, and assess a potential for theft of the merchandise. The computer vision unit can include a camera and an image processor programmed to execute a computer vision algorithm to identify shopping baskets and determine a load status of the basket. The computer vision algorithm can comprise a neural network. The system can identify an at least partially loaded shopping basket that is exiting the store, without indicia of having paid for the merchandise, and execute an anti-theft action, e.g., actuating an alarm, notifying store personnel, activating a store surveillance system, activating an anti-theft device associated with the basket (e.g., a locking shopping cart wheel), etc.

Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

The invention relates to a method of guarding an object or area. The method comprises the steps of scanning an area surrounding the object or area to be guarded using a scanning signal, localizing a moving object detected by the scanning signal, and generating a warning signal only if the detected moving object is localized in a safety zone that is enclosed by a pre-defined contour.

A security system can use video analytics and/or other input parameters to identify a theft event. Optionally, the security system can take remedial action in response. For example, the security system can use video analytics to determine that a person has reached into a shelf multiple times at a rate above a threshold, which can indicate that a thief is quickly removing items from the shelf. The security system can also use video analytics to determine that a person has reached into a shelf via a sweeping action, which can indicate that a thief is gathering and removing a large quantity of items from the shelf in one motion. In response, the security system can alert security personnel, cause a speaker to output an audible message in the target area, flag portions of the video relating to the theft event, activate or ready other sensors or systems, and/or the like.

A process for redacting an image. In operation, an electronic computing device receives an image captured by a camera corresponding to a field of view of the camera. The image contains a plurality of pixels and each pixel in the plurality of pixels capturing a respective region in a plurality of regions of the field of view of the camera. The electronic computing device measures a distance from the camera to each respective region in the plurality of regions of the field of view of the camera. The electronic computing device redacts at least one pixel in the plurality of pixels contained in the image as a function of the distance measured from the camera to a respective region captured in the at least one pixel.

Various embodiments concern a system for monitoring a patient in a bed, the system comprising a camera, a user interface comprising a screen, and a computing system. The computing system can be configured to monitor, with the camera, for motion within each of a plurality of zones, the plurality of zones comprising a one or more inner zones extending adjacent along the bed, one or more outer zones extending adjacent along the one or more inner zones, and one or more end zones. Motion within the inner zones can trigger a fall alert while motion within the outer or end zones can suspend one or more functions to prevent the fall alert from being issued. The end zones can comprise a bottom zone and one or more top zones.

The invention relates to a method for monitoring a monitored region (10) recorded by a camera, wherein a content analysis is performed for a sub-region (20) of the monitored region (10); wherein the sub-region (20) is determined in dependence on one or more parameters; and wherein the determination of the sub-region (20) is performed anew when at least one of the parameters changes during the monitoring.