Abstract: A solution for monitoring an area includes using a region schema for the area. The region schema can include a set of prototypical tracks, each of which includes a start location, an end location, and a trajectory. The trajectory comprises an expected path an object will travel between the start location and the end location and can include variation information that defines an amount that an object can vary from the trajectory. The region schema can be generated by obtaining training object tracking data for the area for an initialization time period and evaluating the object tracking data to identify the set of prototypical tracks. While monitoring the area, monitored object tracking data is obtained for a monitored object in the area, and abnormal behavior of the monitored object is identified when the monitored object tracking data for the monitored object does not follow at least one of the set of prototypical tracks in the region schema.

Abstract: Systems and methods for foreground analysis in real-time video include background subtraction and foreground detection, shadow removal, quick lighting change adaptation, static foreground region detection, foreground fragment reduction, and frame level change detection. Processes include background image extraction and foreground detection, integrating texture information of the background image and a current frame to remove false positive foreground areas resulting from lighting changes, integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows. Static foreground region detection and fragment reduction are also included.

Abstract: A method for real time processing of a sequence of video frames. The video frames are received in synchronization with a recording of the video frames in real time for triggering an alert. The method is implemented by execution of program code on a processor of a computer system. Each frame includes a two-dimensional array of pixels and a frame-dependent color intensity at each pixel. An algorithm determines whether a static object in a current frame of the video frames is an abandoned object or a removed object. The determined status, the current frame time, the static region, and the static object are stored in a data storage medium of the computer system. An alarm is triggered in response to satisfaction of requirements that include a persistence requirement, a non-persistence duration requirement, and a persistence duration requirement.

Abstract: A method for processing a time-ordered sequence of video frames. The method is implemented by execution of program code on a processor of a computer system. Each frame includes a two-dimensional array of pixels and a frame-dependent color intensity at each pixel. A current frame and at least one frame occurring prior to the current frame in the sequence are analyzed via a background subtraction on the at least one frame to determine a background image and a static region mask associated with a static region. The background subtraction determines an existence of a static object relating to the static region. A status of the static object is determined, the status being either that the static object is an abandoned object or that the static object is a removed object. The determined status is stored in a data storage medium of the computer system.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: Systems and methods for foreground analysis in real-time video include background subtraction and foreground detection, shadow removal, quick lighting change adaptation, static foreground region detection, foreground fragment reduction, and frame level change detection. Processes include background image extraction and foreground detection, integrating texture information of the background image and a current frame to remove false positive foreground areas resulting from lighting changes, integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows. Static foreground region detection and fragment reduction are also included.

Abstract: A solution for monitoring an area while accounting for camera motion and/or monitoring tasks is provided. For example, a physical area corresponding to a new field of view can be estimated for a camera for which motion is detected. The physical area can be estimated using a set of reference images previously captured by the camera, each of which comprises a unique field of view previously captured by the camera. Based on the physical area, a status for a monitoring task of the camera (e.g., an alert) can be updated and/or a location of an area for the monitoring task within an image captured by the camera can be updated. Further, based on the update(s), a field of view for a second camera can be automatically adjusted and/or a status for the monitoring task on the second camera can be automatically updated.

Abstract: Methods and apparatus are provided for normalizing objects across a plurality of image viewpoints. A set of classification results are obtained for a given object class across a sequence of images for each of a plurality of viewpoints. The classification results are each comprised of a position of one of the objects in the image, and at least one projected property of the object at that position. Normalization parameters are then determined for each of the viewpoints by fitting a high order model to the classification results to model a change in the projected property. The high order model may implement a least squares fit of a second order polynomial to the classification results. The normalization parameters may be used to compute normalized features and normalized training data for object classification.

Abstract: A surveillance system and method includes a plurality of sensors configured to monitor an environment. A plurality of analytic engines is associated with each of the plurality of sensors. The plurality of analytic engines employs different technologies and is configured to analyze input from the sensors to determine whether an event has occurred in a respective technology. A unifying data model is configured to cross correlate detected events from the different technologies to gain integrated situation awareness across the different technologies.

Abstract: A system and method for generating a viewable video index for low bandwidth applications are provided. The exemplary aspects of the present invention solve the problems with the prior art systems by incorporating information for generating a viewable representation of the video data into the index, thus generating a viewable video index. The viewable video index contains information for generating a visual representation of moving objects in the video data, a visual representation of the background of the video capture area, i.e. the scene, a representation of the object trajectory, a representation of the object attributes, and a representation of detected events. The result is that the viewable video index may be transmitted to a low bandwidth application on a client device and may be used along with associated object and background models to generate a representation of the actual video data without requiring that the original video data itself be streamed to the client device.

Abstract: A system for automatically acquiring high-resolution images by steering a pan-tilt-zoom camera at targets detected in a fixed camera view is provided. The system uses automatic or manual calibration between multiple cameras. Using automatic calibration, the homography between the cameras in a home position is estimated together with the effects of pan and tilt controls and the expected height of a person in the image. These calibrations are chained together to steer a slave camera. The manual calibration scheme steers a camera to the desired region of interest and calculates the pan, tile and zoom parameters accordingly.

Abstract: A data indexing system and method includes acquiring activity data in a context and indexing the activity data in accordance with contextual conditions. The activity data is stored in accordance with indices. An event is correlated with the activity data by using the indices to review the activity data in the context.

Abstract: An occlusion detection system and method include a decomposer configured to decompose an image into a set of hierarchical parts. A hierarchy of classifiers is employed to detect features in the image and the hierarchical parts. A logical operation is configured to logically combine a classification result from at least two of the classifiers to detect an occlusion state of the image.

Abstract: An approach that manages moving surveillance cameras is described. In one embodiment, there is a system for managing images generated from a movable camera. In this embodiment, the system comprises a motion estimation component configured to determine camera motion. A camera motion alert component is configured to generate an alert in response to a determination that the camera has moved or the camera has ceased moving.

Abstract: In general, the present invention allows any number of sequential filter graphs to be created based on a pub-sub architecture/model. Specifically, under the present invention, the filters (components) will publish their ideal priorities of accessing data source, an ideal input data type, and a unique alternative input data type. A mechanism such as a queue manager will receive the publication(s) and determine an appropriate order/sequence of the filters based on their ideal priorities. The queue manager will also assign an output data type to each filter (an optionally an alternative output data type) based on the ideal input types specified in the publish messages. The queue manager will then transmit messages (e.g., a subscribe message) to the filters with the determined order and assigned data types.

Abstract: A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.

Abstract: A system, method and program product for providing a video surveillance system that enhances object detection by utilizing feedback from a tracking system to an object detection system. A system is provided that includes: a moving object detection system for detecting moving objects in a video input; an object tracking system for tracking a detected moving object in successive time instants; and a tracker feedback system for feeding tracking information from the object tracking system to the moving object detection system to enhance object detection.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: A system and method to estimate the absolute coarse pose of a rigid body, and more specifically of an individual's head as captured by overhead wide-angle cameras, by integrating position and pose information. Position information ideally includes three-dimensional position information provided by range finders or derived from images captured by multiple cameras. The three-dimensional position information can additionally be employed to determine the anchored viewing ray for the object.