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: 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: The system and method obscures descriptive image information about one or more images. The system comprises a selector for selecting the descriptive image information from one or more of the images, a transformer that transforms the descriptive information into a transformed state, and an authorizer that provides authorization criteria with the image. In a preferred embodiment, the transformed state is the respective image encoded with the descriptive information. The descriptive information can be obscured so that the descriptive information in the transformed state can be decoded only if one or more authorization inputs satisfy the authorization criteria.

Abstract: An apparatus and method of identifying objects with salient motion in a scene and program product therefor. A region of change is identified within a scene. Optical flow is determined for the region of change. Pixels moving in a common direction are identified as seed pixels. Seed pixels are expanded to form pixel clusters. Temporal imaging results are fused to identify those objects with salient motion.

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 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: 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 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 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.

Abstract: A system and method for automatic detecting neutral expressionless faces in digital images and video is described. First a face detector is used to detect the pose and position of a face and find the facial components. Second, the detected face is normalized to a standard size face. Then a set of geometrical facial features and three histograms in zones of mouth are extracted. Finally, by feeding these features to a classifier, the system detects if there is the neutral expressionless face or not.

Abstract: A system and method for selectively monitoring movement of one or more objects having one or more object attributes in a three dimensional space. The method is achieved by following the steps of detecting a position of the one or more objects in the three dimensional space by collecting information from one or more static sensors; selecting each detected object for monitoring; uniquely identifying selected objects and assigning one or more variable sensors to monitor the uniquely identified object. The method further requires gathering information from the variable sensors for each identified object; detecting a direction of each identified object in the three dimensional space; and controlling the one or more variable sensors to continuously point to the assigned uniquely identified object.

Abstract: The system and method obscures descriptive image information about one or more images. The system comprises a selector for selecting the descriptive image information from one or more of the images, a transformer that transforms the descriptive information into a transformed state, and an authorizer that provides authorization criteria with the image. In a preferred embodiment, the transformed state is the respective image encoded with the descriptive information. The descriptive information can be obscured so that the descriptive information in the transformed state can be decoded only if one or more authorization inputs satisfy the authorization criteria.

Abstract: A system and method for automatic detecting neutral expressionless faces in digital images and video is described. First a face detector is used to detect the pose and position of a face and find the facial components. Second, the detected face is normalized to a standard size face. Then a set of geometrical facial features and three histograms in zones of mouth are extracted. Finally, by feeding these features to a classifier, the system detects if there is the neutral expressionless face or not.