The present invention provides a monitor for dynamic displaying. K cameras are connected with the monitor in order to display images recorded by the k cameras on a screen of the monitor. An “abnormality detection algorithm” is used for detecting abnormalities of the images recorded by the k cameras. Those images having abnormalities are displayed continuously on the screen, other images having no abnormality are not displayed, so that a security service personnel can watch those images having abnormalities on the screen to enable appropriate action quickly.

In a video surveillance system, confirming videos from plurality of cameras causes a heavy burden on surveillance officers, and it is difficult to select a suitable video for observation. A video surveillance system includes a plurality of cameras which pick up images in a surveillance area, and a recognition unit which detects an object from videos acquired by the plurality of cameras. In the case where an object is detected in a surveillance area where images are picked up duplicately by the plurality of cameras, the recognition unit acquires a recognition result that is a feature quantity of the object for each camera. A display selection unit is, provided which, on the basis of the recognition result and a degree of priority of the recognition result, prioritizes the video from each of the cameras according to the degree of priority.

Methods, systems, and apparatus, including computer programs encoded on storage devices, for monitoring, security, and surveillance of a property. In one aspect, a system includes a virtual reality headset, a plurality of cameras, a plurality of sensors that includes a first sensor, a control unit, wherein the control unit includes a network interface, a processor, a storage device that includes instructions to perform operations that comprise receiving data from the first sensor that is indicative of an alarm event, determining a location of the first sensor, identifying a set of one or more cameras from the plurality of cameras that are associated with the first sensor, selecting a particular camera from the identified set of one or more cameras; and transmitting one or more instructions to the particular camera that command the particular camera to stream a live video feed to a user interface of the virtual reality headset.

An alert generation method and system. The method includes receiving by a computer processor, alert data indicating filters for specified alert types associated with possible future events. The computer processor receives monitor definition data and media generated audio/video data; compares the alert data to the media generated audio/video data; determines a first alert type matches first audio/video data of the media generated audio/video data; and determines that the first audio/video data comprises a primary event. The computer processor broadcasts the primary event.

An image monitoring system includes a recorder that records an image captured by a camera via a network. The system is controlled to display the present image captured by the camera or a past image recorded on the recorder. A moving object is detected from the image captured by the camera, the detector including a resolution converter for generating an image with a resolution lower than the resolution of the image captured by the camera. A moving object is detected from the image generated by the resolution converter and positional information on the detected moving object is output. The positional information of the detected moving object is merged with the image captured by the camera on the basis of the positional information.

Monitoring systems and methods for use in security, safety, and business process applications utilizing a correlation engine are disclosed. Sensory data from one or more sensors are captured and analyzed to detect one or more events in the sensory data. The events are correlated by a correlation engine, optionally by weighing the events based on attributes of the sensors that were used to detect the primitive events. The events are then monitored for an occurrence of one or more correlations of interest, or one or more critical events of interest. Finally, one or more actions are triggered based on a detection of one or more correlations of interest, one or more anomalous events, or one or more critical events of interest. A hierarchical storage manager, having access to a hierarchy of two or more data storage devices, is provided to store data from the one or more sensors.

A computer-implemented method for monitoring activity at a location, provides receiving a first data signal and a second data signal, wherein the first and second data signals are related to activities detected at a location, and reproducing the first and second data signals in a chronology that indicates relative timing of receipt of the first and second data signals via a user interface. This may accelerate review and inspection of multiple data signals recorded over time, including data signals of various types. The coincidence of patterns in the data signals may be detected and brought to the user's attention for closer review, such as via transmission of a message or transmission of a segment of recorded data.

System for monitoring at least one observation area including at least one camera for providing panorama pictures of the at least one area, where the camera is arranges on a rotating platform in the at least one area to be monitored; at least one video camera for providing real time video and which is arranged on a stationary platform in the at least one area to be monitored; a processing device connected to the camera and the video camera for capturing, processing and coordinating signals.

A video processing apparatus includes a video analyzer that analyzes video data captured by a surveillance camera, detects an event belonging to a specific category, and outputs a detection result, a display controller that displays, together with a video of the video data, a category setting screen for setting a category of an event included in the video, and a learning data accumulator that accumulates, as learning data together with the video data, category information set in accordance with an operation by an operator to the category setting screen. The video analyzer performs learning processing by using the learning data accumulated in the learning data accumulator.