A system provides a transformed video stream from, a publicly or privately owned and operated camera bearing on an in-scope location vicinity, to, a responding emergency service agency (ESA). A request from an emergency services agent's display terminal includes location indicia and elicits a map of cameras bearing on the location vicinity as well as other display terminals in the area. Upon request, an application programming interface enables a video stream to comply with the privacy and access settings of the camera owner/operators. A plurality of private and public security surveillance cameras is coupled to a server. Exterior/street view video images are streamed to the server which may contact an owner for emergency access. An emergency agency vehicle at a location has a display for a selected gallery of obfuscated exterior/street views from cooperative networks of public and private security cameras bearing on the vicinity of an incident.

Systems and methods are disclosed and an example system includes a digital image receiver for receiving a digital image, and an automatic obscuration processor coupled to the image receiver and configured to determine whether the digital image includes a region that classifies as an image of a category of object and, upon a positive determination, to obscure the region and output a corresponding obscured-region digital image.

A surveillance monitoring system may use a camera to detect any viewing faces visible within viewing sight of a monitor and determine whether the detected viewing faces belong to authorized individuals who are authorized to view video surveillance footage on the monitor or if any of the detected viewing faces belong to individuals who are not authorized to view video surveillance footage on the monitor. When the detected viewing faces belong only to authorized individuals, the surveillance monitoring system continues to display the video surveillance footage that includes identifiable faces without anonymizing the identifiable faces. When the detected viewing faces also include unauthorized individuals, the surveillance monitoring system may continue to display the video surveillance footage, but the surveillance monitoring system may automatically anonymize one or more of the identifiable faces seen in the video surveillance footage.

The application is directed at a method and system for selective anonymization, wherein the method comprises the steps of capturing visual streaming data, identifying an anonymizable object in the visual data, for which a quantized identity (y) and an individual private key (n) is determined. Based on the individual private key (n) and the quantized identity (y), the first set of encryptions (E1) is calculated, comprising at least two distinct encryptions of the quantized identity. The first set of encryptions (E1) of the quantized identity (y) is sent to a central server, which, in return, sends an exception information indicating if an exception list of the central server comprises a set of exception encryptions (E2) which corresponds to the first set of encryptions (E1). The anonymizable object is then selectively anonymized in the streaming visual data depending on the exception information and an operating mode of the edge device, thereby generating selectively modified visual streaming data and the selectively modified visual streaming data is transmitted to a remote database.

In some embodiments, a data-secure sensor system includes one or more processors configured to receive sensor data (e.g., image data, audio data, etc.) and generate descriptive data based on the sensor data that corresponds to a physical area that corresponds to information about identified objects or activity in physical area, an input/output (I/O) port, and an I/O choke communicatively coupled between the one or more processors and the I/O port, the I/O choke configured to limit a communication bandwidth of the I/O port to a maximum data rate. The one or more processors can be configured to prevent the sensor data from being accessible via any external port of the data-secure camera system, including the I/O port, and allow the descriptive data to be accessible via the I/O port.

An intrusion detection system detects when an unexpected person enters the environment of a user who is in a meeting. A privacy protection action which is an action that is to be taken in response to the detected intrusion, is identified. Audio and/or video systems are then controlled to perform the privacy protection action. Machine learning can be used, based upon user interactions, to improve intrusion detection and other parts of the system.

The present disclosure generally relates to the field of camera surveillance, and in particular to a method and control unit for controlling a bitrate of a video stream captured with an image acquisition device.

Displayed is a flow line analysis image in which the privacy of a person reflected in a wide imaging region is appropriately protected, and staying information or passing information of a person in the wide imaging region can be easily and accurately recognized. A camera includes an imaging section that captures an image of a differing imaging region for each camera, a background image generating section that repeatedly generates a background image of a captured image of the imaging region at predetermined timings, a flow line information analyzing section that extracts flow line information regarding a staying position or a passing position of a moving object in the imaging region of the camera, included in the captured image, and a transmitter that transmits the background image and the flow line information of the moving object to a server at a predetermined transmission cycle. A server includes an image generating section that acquires flow line analysis images based on superimposition between the background image of the captured image and the flow line information of the moving object for each camera, and generates a wide-region flow line analysis image by using the plurality of acquired flow line analysis images, and a display control section that displays the wide-region flow line analysis image on a display section.

Methods, systems, apparatus, and computer programs, for tracking objects are disclosed. In one aspect, a method is disclosed that includes actions of obtaining an image, determining that a user of a first monitoring system has opted-in for object tracking by a second monitoring system that is remote from the first monitoring system, and based on a determination that the user of the first monitoring system has opted-in for object tracking: determining whether the obtained image satisfies a predetermined level of similarity to a stored tracking object image model stored on a first device of the first monitoring system, and based on a determination that the obtained image satisfies a predetermined level of similarity to the stored tracking object image model, generating a tracking update notification, and transmitting the tracking update notification to the second monitoring system that is remote from the first monitoring system.

An apparatus including an interface and a processor. The interface may be configured to receive pixel data generated by a capture device. The processor may be configured to generate video frames in response to the pixel data, perform computer vision operations on the video frames to detect objects, perform a classification of the objects detected based on characteristics of the objects, determine whether the classification of the objects corresponds to a user-defined event and a user-defined identity and generate encoded video frames from the video frames. The encoded video frames may comprise a first sample of the video frames selected at a first rate when the user-defined event is not detected and a second sample of the video frames selected at a second rate while the user-defined event is detected. The video frames comprising the user-defined identity without a second person may be excluded from the encoded video frames.