A method for masking of objects in a video stream, the method comprising: acquiring a video stream; detecting an object in the video stream; determining whether the detected object belongs to a foreground of the video stream indicative of moving objects or to a background of the video stream indicative of static objects; classifying the detected object to be of a specific type using a first classifier if the detected object is determined to belong to the foreground, and using a second classifier if the detected object is determined to belong to the background, the first classifier being different from the second classifier, and if the detected object is classified as being of the specific type of object, masking the object in the video stream.

An image processing method is provided. The method includes acquiring a video. The method includes using an object detection engine to detect a person in the video. The object detection engine is integrated with an image signal processing pipeline. The method includes transmitting the video over a network. The method includes determining that the detected person has moved less than a pre-set distance. The method includes, responsive to the determining, pausing transmission of the video. An embedded image processor including an object detection engine is also provided.

A non-lethal dazzling turret includes a laser operable in the visible spectrum. The non-lethal dazzling turret can be deployed, for example, behind a counter at a convenience store or a gas station, and can include a camera as well as an on-board computer. The non-lethal dazzling turret can stream video to a remote location where an operator can aim and fire the non-lethal dazzling turret at potential targets as needed. Alternatively, a fully autonomous version is disclosed that can be activated by, for example, a panic button.

The present disclosure describes a system and method designed to protect the contents of a region or space within a facility (e.g., building, home, vehicle, outdoor space, etc.). The system is configured to identify an area to be protected (e.g., nightstand, medicine cabinet, safe), monitor surroundings, and manage and deploy response(s) to threats to the region or space under protection. The system may also be configured to provide incremental warnings, interventions, or countermeasures to deter people or animals from accessing the Protected Space.

This document describes techniques, apparatuses, and systems for batch size adjustment using latency-critical event recognition. The techniques described herein enable an electronic device (e.g., security camera) to determine the likelihood of an event of interest (e.g., latency-critical event) occurring in data (e.g., audio and/or video) captured by the electronic device. To make such a determination, the electronic device may switch upload modes to upload the data, using a different batch size to reduce latency, to another device for user access, based on the likelihood of an event of interest occurring in the data. In this way, the techniques, apparatuses, and systems for batch size adjustment using latency-critical event recognition provide an efficient way to provide all-day security monitoring.

A low or medium voltage switchgear monitoring system includes: at least one sensor; a processing unit; and an output unit. The at least one sensor acquires sensor data within a compartment of a switchgear. The sensor data includes first sensor data. The sensor data includes second sensor data. The second sensor data is acquired a set time after the first sensor data. The at least one sensor provides the first sensor data and the second sensor data to the processing unit. The processing unit determines status information for a compartment of the switchgear based on a comparison of the second sensor data to the first sensor data. The output unit outputs the status information.

A building monitoring system includes a first sensor configured to detect a first condition in the space, a second sensor configured to detect a second condition in the space, and a robotic sentinel. The robotic sentinel includes a memory for storing one or more rules each configured to identify an alert condition for the space based on the first and/or second conditions in the space, a communications module configured to communicate with a remote device over a network, and a controller operatively coupled to the sensors, the memory, and the communications module. The controller is configured to apply the one or more rules to the first and second detected conditions in the space to identify one or more alert conditions and determine what action is required by the robotic sentinel, and if action is required, command the robotic sentinel to travel to a location of the alert condition.

A processing system including at least one processor may monitor a condition of a premises during a time period via at least one sensor, where at least one user is permitted a use of the premises during the time period, detect a change in the condition of the premises during the time period via the at least one sensor, determine a violation of at least one rule relating to the use of the premises by the at least one user, wherein the violation is indicated by the change in the condition, and generate an alert of the violation of the at least one rule relating to the use of the premises by the at least one user.

A method and a motion data extraction and vectorization system (MDEVS) extract and vectorize motion data of an object in motion with optimized data storage and data transmission bandwidth. The MDEVS includes an image sensor, a motion data processor, and a storage unit. The image sensor captures video data including a series of image frames of the object in motion. The motion data processor detects an object in motion from consecutive image frames, extracts motion data of the detected object in motion from each image frame, and generates a matrix of vectors defining the object in motion for each image frame using the extracted motion data. The motion data includes, for example, image data of the object, trajectory data, relative physical dimensions, a type of the object, time stamp of each image frame, etc. The storage unit maintains the generated matrix of vectors for local storage, transmission, and analysis.

A vehicle information acquiring unit for acquiring vehicle information; a heat source information acquiring unit for acquiring heat source information; a stop determining unit for determining whether or not a vehicle is stopped on the basis of the vehicle information; a heat source determining unit for determining whether or not a heat source satisfying a target condition is generated in the vehicle on the basis of the heat source information, when the stop determining unit determines that the vehicle is stopped; an activation control unit for activating an imaging device, when the heat source determining unit determines that a heat source satisfying the target condition is generated; an image acquiring unit acquiring a captured image of inside of the vehicle from the imaging device; and a notification control unit outputting notification information to the outside of the vehicle, when a living body is detected in the captured image.