Methods, systems, and apparatus for camera detection of human activity with co-occurrence are disclosed. A method includes detecting a person in an image captured by a camera; in response to detecting the person in the image, determining optical flow in portions of a first set of images; determining that particular portions of the first set of images satisfy optical flow criteria; in response to determining that the particular portions of the first set of images satisfy optical flow criteria, classifying the particular portions of the first set of images as indicative of human activity; receiving a second set of images captured by the camera after the first set of images; and determining that the second set of images likely shows human activity based on analyzing portions of the second set of images that correspond to the particular portions of the first set of images classified as indicative of human activity.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, a request for a location of an item is obtained. Current video data from one or more cameras is obtained. It is determined that the item is not shown in the current video data. Sensor data corresponding to historical video data is obtained. Events that likely occurred with the item and corresponding likelihoods for each of the events are determined. A likely location for the item is determined based on the likelihoods determined for the events. An indication of the likely location of the item is provided.

Methods and systems for detecting and predicting anomalies include processing frames of a video stream to determine values of a feature corresponding to each frame. A feature time series is generated that corresponds to values of the identified feature over time. A matrix profile is generated that identifies similarities of sub-sequences of the time series to other sub-sequences of the feature time series. An anomaly is detected by determining that a value of the matrix profile exceeds a threshold value. An automatic action is performed responsive to the detected anomaly.

Multiple cameras capture videos within a secure room. When individuals are detected as entering the room, identities of the individuals are resolved. When an asset is exposed in a field of view of one of the cameras, the individuals' eye and head movements are tracked from the videos with respect to one another and the asset. Additionally, touches made by any of the individuals on the asset are tracked from the videos. The eye and head movements are correlated with the touches or lack of touches according to a security policy for the asset. Any violations of the security policy are written to a secure audit log for the room and the asset.

The present application discloses an intelligent processing method and system for video data, wherein, in the method an intelligent camera set a warning rule, the method comprises: the intelligent camera collecting video data and analyzing the collected video data in real time, generating intelligent data if the warning rule is met, which intelligent data contain an encoder identifier and motion trajectory information; the intelligent camera packaging the video data and the intelligent data into a program stream and sending it to a frame analyzing component in a cloud storage system; the frame analyzing component unpacking the received program stream to obtain the video data and the intelligent data, and storing the video data and the intelligent data in storage components respectively; the storage components sending storage address information of the video data and the intelligent data to an index server for recording respectively. The solutions of the present application can perform intelligent processing for the collected video data in real time.

Systems and methods for detecting potential theft and identifying individuals having a history of committing theft use an electromagnetic emission associated with a personal electronic device associated with an individual is received from at least one of a sensor that is coupled to at least one of a traffic camera or an aerial drone camera. One or more signal properties of the electromagnetic emission are analyzed to determine an emission signature. Video data and video analytics are correlated with the emission signature to identify the individual having possession of the item. The emission signature and video data are stored for later use during a checkout procedure. If an emission signature detected at a checkout station matches that of the individual having possession of the item, and the item is not processed through the checkout station, an alert is issued and the individual is flagged as a potential shoplifter.

An intruder location-based dynamic virtual fence configuration and a multiple image sensor device operation method are provided. A method of detecting an intruder based on a virtual fence includes detecting an intruder invading a virtual fence set in a protection area by using a first image sensor device, and tracking the intruder through cooperation with second image sensor devices adjacent to the first image sensor device, based on information of the intruder.

The disclosure relates improving correctional officer safety. A system can include a first camera facing a region of a correctional facility including monitored objects, the first camera configured to generate first pixel data including first pixels corresponding to the objects, a second camera in the correctional facility and facing away from the region, the second camera configured to generate second pixel data including second pixels corresponding to a person that approaches the region, and a server configured to receive the first and second pixel data through a network connection, transmit the received data to a recognition service through the network, and receive an alert from the alert service that indicates a monitoring rule associated with an object of the objects is violated, an identification associated with the person, a last known location of the person or the object, and an indication of the monitoring rule violated.

The present invention relates to an intruder deterrent system. The system is comprised of a deterrent device is further comprised of a camera, a speaker, and a light. An area can be monitored by a user using the camera such that a user can deter an intruder by producing a loud sound from the speaker and by causing the light to strobe.

Disclosed herein are an apparatus, method, and computer-readable medium for detecting an anomalous behavior event for an environment and transmitting an alert of the event. An implementation may comprise detecting, in a plurality of image frames captured by a camera, when a person enters a region of interest, tracking movements of the person in the region of interest by comparing images of the person in the plurality of image frames, determining attributes of the person, determining environmental contexts for the region of interest, determining whether or not an anomalous behavior is detected based on the movements and the attributes of the person and the environmental contexts, generating an alert when the anomalous behavior is detected, and transmitting the generated alert to user devices of one or more predetermined recipients.