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 extracted video primitives and event occurrences may be used to create and define additional video analytic rules. The system can undertake a response, such as an alarm, based on extracted event occurrences.

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 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.

Abstract: A system for video monitoring a retail business process includes a video analytics engine to process video obtained by a video camera and generate video primitives regarding the video, A user interface is used to define at least one activity of interest regarding an area being viewed, each activity of interest identifying at least one of a rule or a query regarding the area being viewed. An activity inference engine processes the generated video primitives based on each defined activity of interest to determine if an activity of interest occurred in the video.

Abstract: The automatic generation of one or more secondary video streams based on an input primary video stream may use analytics performed on the video to provide information on targets, events, and/or areas of interest to permit the one or more secondary video streams to concentrate on one or more targets, events, and/or areas of interest.

Abstract: Video processing to detect a stationary object in a video includes: performing background change detection on the video; performing motion detection on the video; determining stable pixels in the video based on the background change detection; and combining the stable pixels to identify at least one stationary object in the video.

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 method of video processing may include registering one or more frames of input video received from a sensing unit, where the sensing unit may be capable of operating in a scanning mode. The registration process may project the frames onto a common reference. The method may further include maintaining a scene model corresponding to the sensing unit's field of view. The method may also include processing the registered frames using the scene model, where the result of processing the registered frames includes visualization of at least one result of processing.

Abstract: A video surveillance system may include at least one sensing unit capable of being operated in a scanning mode and a video processing unit coupled to the sensing unit, the video processing unit to receive and process image data from the sensing unit and to detect scene events and target activity.

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: 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 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 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 method of video surveillance may include pre-processing video data to obtain foreground edge information for at least one frame of said video data. The method may perform line segment detection on said foreground edge information to obtain one or more line segments. The line segment detection may be performed by means of an algorithm in which edge pixels are searched and line segments found are checked for validity. It may detect and track one or more targets based on said one or more line segments and may determine if at least one predetermined event is present in said at least one frame of said video data based on the detecting and tracking of said one or more targets.

Abstract: A video-based human verification system and method may include a video sensor adapted to obtain video and produce video output. The video sensor may include a video camera. The video-based human verification system may further include a processor adapted to process video to verify a human presence. An alarm panel may be coupled to the video sensor, the alarm panel being adapted to receive video output or alert information from the video sensor.

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: An input video sequence may be processed by processing the input video sequence to obtain target information; and building at least one target property map based on said target information. The target property map may be used to detect various events, particularly in connection with video surveillance.

Abstract: An input video sequence may be processed by processing the input video sequence to obtain target information; and building at least one path model based on said target information. The path model may be used to detect various events, particularly in connection with video surveillance.

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 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.