Abstract: A video surveillance system is set up, calibrated, tasked, and operated. The system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Abstract: A method of operating a video surveillance system is provided. The video surveillance system including at least two sensing units. A first sensing unit having a substantially 360 degree field of view is used to detect an event of interest. Location information regarding a target is sent from the first sensing unit to at least one second sensing unit when an event of interest is detected by the first sensing unit.

Abstract: A video surveillance system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Abstract: A method of video analysis may comprise tracking a state of each target in a video through multiple frames of said video, each state indicating a visibility condition of a target.

Abstract: A computer-based method for automatic detection of water regions in a video include the steps of estimating a water map of the video and outputting the water map to an output medium, such as a video analysis system. The method may further include the steps of training a water model from the water map; re-classifying the water map using the water model by detecting water pixels in the video; and refining the water map.

Abstract: A method of video processing may include analyzing input video information to determine if a current video frame is directed to a same view as a previous video frame; determining whether a new view is present; and indicating a need to use video processing information pertaining to the new view if a new view is determined to be present.

Abstract: A method of video processing may include analyzing input video information to determine if a current video frame is directed to a same view as a previous video frame; determining whether a new view is present; and indicating a need to use video processing information pertaining to the new view if a new view is determined to be present.

Abstract: In one exemplary embodiment a method calibrates a pan-tilt-zoom (PTZ) camera system. The PTZ camera system may include a PTZ camera. The method may perform at least one of the following steps: determining a radial distortion of the PTZ camera; determining a base focal length of the PTZ camera; determining a zoom and magnification profile of the PTZ camera; determining an actuation delay of the PTZ camera system; determining a pan position mode speed and/or a tilt position mode speed of the PTZ camera; determining a pan velocity profile and/or a tilt velocity profile of the PTZ camera; determining a zoom position profile and/or a zoom duration profile of the PTZ camera; determining a query delay of the PTZ camera system; and determining a minimum query interval of the PTZ camera system.

Abstract: A video surveillance system is set up, calibrated, tasked, and operated. The system extracts video primitives and extracts event occurrences from the video primitives using event discriminators. The system can undertake a response, such as an alarm, based on extracted event occurrences.

Abstract: A method for segmenting video data into foreground and background (324) portions utilizes statistical modeling of the pixels ? statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared (326) with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system The method for segmenting video data may be implemented in hardware.

Abstract: Input video data is processed to detect a change in a posture of a person shown in the video data. The change of posture may be the result of an event, for example, the person falling or getting up. The input video data may include a plurality of frames. Objects in the frames are tracked and then classified, for example, as human and non-human targets. At least one of the position or location of a human target in the frames is identified. Changes in the location or position of the human target between the frames is determined. When the change in at least of the position or location exceeds a predetermined threshold, a falling down event or a getting up event is detected. The changes in the position or location of the human target can be determined based on a number of different factors.

Abstract: A method of video surveillance may include performing on input video at least one of the operations selected from the group consisting of motion detection and change detection, recording a motion pattern based on a result of said at least one of the operations, and analyzing the motion pattern to detect periodic motion in the video. A video surveillance apparatus may include a change detector, a motion detector, and/or a combination motion/change detector, a pattern analyzer, and a periodic motion detector.

Abstract: A computer-readable medium contains software that, when read by a computer, causes the computer to perform a method for wide-area site-based surveillance.

Abstract: A computer-based system for performing scene content analysis for human detection and tracking may include a video input to receive a video signal; a content analysis module, coupled to the video input, to receive the video signal from the video input, and analyze scene content from the video signal and determine an event from one or more objects visible in the video signal; a data storage module to store the video signal, data related to the event, or data related to configuration and operation of the system; and a user interface module, coupled to the content analysis module, to allow a user to configure the content analysis module to provide an alert for the event, wherein, upon recognition of the event, the content analysis module produces the alert.

Abstract: A computer-readable medium contains software that, when read by a computer, causes the computer to perform a method for wide-area site-based surveillance.

Abstract: A video sequence of a field of view within an environment is received. Targets are detected in the video sequence. Target geo-positional information is received. Correspondences between the targets detected in the video sequence and the target geo-positional information are determined and used to calibrate the camera and to geo-register a field of view of the camera.

Abstract: A method for segmenting video data into foreground and background portions utilizes statistical modeling of the pixels. A statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system. The method for segmenting video data may be implemented in hardware.

Abstract: A video imager may be used to measure the natural and/or artificial light levels in a space. The lighting estimates may be passed to a controller via a communication network. The lighting estimates may be in the form of actual radiance values, brightness, or other forms. The controller may determine if and which areas of the space require more light or if and which areas of the space have more light than required. Based on the lighting estimates, the controller may issue commands to turn on/off or dim/brighten the light from various ones or combinations of light sources in or around the space via actuators. The controller may also directly interface with the light sources.

Abstract: A system for detecting behavior of a target may include: a target detection engine, adapted to detect at least one target from one or more objects from a video surveillance system recording a scene; a path builder, adapted to create at least one mature path model from analysis of the behavior of a plurality of targets in the scene, wherein the at least one mature path model includes a model of expected target behavior with respect to the at least one path model; and a target behavior analyzer, adapted to analyze and identify target behavior with respect to the at least one mature path model. The system may further include an alert generator, adapted to generate an alert based on the identified behavior.

Abstract: A video surveillance system comprises a first sensing unit; a second sensing unit; and a communication medium connecting the first sensing unit and the second sensing unit. The first sensing unit provides information about a position of a target to the second sensing unit via the communication medium, and the second sensing unit uses the position information to locate the target.