Abstract: A system, method and computer program product for mining a rule including spatial information and non-spatial information by using a SAR (Spatial Association Rule) mining tool. The computing system is configured to construct an expanded spatial predicate transaction table for reference spatial objects and a generalized taxonomy for task-relevant spatial objects. The computing system is configured to run the SAR mining tool with the constructed expanded spatial predicate transaction and the generalized taxonomy. The computing system outputs, from the SAR mining tool, a set of generalized spatial association rules for the reference spatial objects. The generalized spatial association rule includes the spatial information and non-spatial information, associated with both the reference spatial objects and the task-relevant spatial objects.

Abstract: Techniques for performing visual surveillance of one or more moving objects are provided. The techniques include registering one or more images captured by one or more cameras, wherein registering the one or more images comprises region-based registration of the one or more images in two or more adjacent frames, performing motion segmentation of the one or more images to detect one or more moving objects and one or more background regions in the one or more images, and tracking the one or more moving objects to facilitate visual surveillance of the one or more moving objects.

Abstract: Techniques for automatically calibrating one or more regions of interest for video surveillance are provided. The techniques include at a user-defined frequency, determining if one or more regions of interest (ROIs) are present within a field of view of a camera, if one or more ROIs are present within the field of view of the camera, automatically calibrating the one or more ROIs within the field of view of the camera, and if one or more ROIs are not present within the field of view of the camera, sending an alert to a user.

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 method and system for real time processing of a sequence of video frames. A current frame in the sequence and at least one frame in the sequence occurring prior to the current frame is analyzed. Each frame includes a two-dimensional array of pixels. The sequence of video frames is received in synchronization with a recording of the video frames in real time. The analyzing includes performing a background subtraction on the at least one frame, which determines a background image and a static region mask associated with a static region consisting of a contiguous distribution of pixels in the current frame. The static region mask identifies each pixel in the static region upon the static region mask being superimposed on the current frame. The background image includes the array of pixels and a background model of the at least one frame and does not include any moving object.

Abstract: Principles of the invention provide techniques for analyzing spatiotemporally ambiguous events. In one aspect, an exemplary method includes the steps of storing event data representative of an event, the event data comprising spatiotemporally ambiguous measurements; storing side information, the side information comprising at least one of spatial data and temporal data related to the event in space-time: associating the event data with the side information by soft association to form association data; applying one or more estimation techniques to the association data to form estimation data; and determining at least one of a rate, a factor, a likelihood, a value, a time, a location, and a cause for the event by applying one or more characterization techniques to the estimation data.

Abstract: A method for determining a maintenance schedule of geographically dispersed physical assets includes receiving asset data including infrastructure relationships between the assets, modeling failure risk of the assets based on spatial, temporal and network relationships, and producing the maintenance schedule according to a combination of the risk model, asset data, maintenance, and external operation constraints. The maintenance schedule may be corrective and/or strategic.

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 allows for model based people counting is provided. In one embodiment, there is a generating tool configured to generate a set of person-shape models based on results of a cumulative training process; a detecting tool configured to detect persons in a camera field-of-view by using the set of person-shape models, and a counting tool configured to track detected persons upon crossing by the detected persons of a previously established virtual boundary.

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: Techniques for classifying one or more objects in at least one video, wherein the at least one video comprises a plurality of frames are provided. One or more objects in the plurality of frames are tracked. A level of deformation is computed for each of the one or more tracked objects in accordance with at least one change in a plurality of histograms of oriented gradients for a corresponding tracked object. Each of the one or more tracked objects is classified in accordance with the computed level of deformation.

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: The present invention provides an approach for rewarding customers for use of self-checkout stations and, optionally, for being self-sufficient in such use by not requiring retailer (employee) assistance. Specifically, the under the present invention, a set of service choices made by a customer during purchasing transactions are tracked. Such service choices include whether the customer elected to use self-checkout stations. In addition, a frequency of assistance needed by the customer during the purchasing transactions will be tracked. Such tracking can be accomplished using any known technology including the use of the customer loyalty cards that are assigned to specific customers. In any event, a reward can be offered to the customer if the customer elected to use self-checkout stations to complete at least a subset of the purchasing transactions, and/or if the frequency of assistance needed by the customer during the purchasing transactions fell below a predetermined threshold.

Abstract: A method, information processing system, and computer program storage product annotate video images associated with an environmental situation based on detected actions of a human interacting with the environmental situation. A set of real-time video images are received that are captured by at least one video camera associated with an environment presenting one or more environmental situations to a human. One or more user actions made by the human that is associated with the set of real-time video images with respect to the environmental situation are monitored. A determination is made, based on the monitoring, that the human driver has one of performed and failed to perform at least one action associated with one or more images of the set of real-time video images. The one or more images of the set of real-time video images are annotated with a set of annotations.

Abstract: Techniques for detecting one or more events are provided. The techniques include using multiple overlapping regions of interest on a video sequence to cover a location for one or more events, wherein each event is associated with at least one of the multiple overlapping regions of interest, applying multiple-instance learning to the video sequence to select one or more of the multiple overlapping regions of interest to construct one or more location-aware event models, and applying the models to the video sequence to detect the one or more events and to determine the one or more regions of interest that are associated with the one or more events.

Abstract: Techniques for detecting one or more events are provided. The techniques include using one or more regions of interest on a video sequence to cover a location for one or more events, wherein each event is associated with at least one of the one or more regions of interest, applying multiple-instance learning to the video sequence to construct one or more location-aware event models, and applying the models to the video sequence to determine the one or more regions of interest that are associated with the one or more events.

Abstract: A method, information processing system, and computer program storage product annotate video images associated with an environmental situation based on detected actions of a human interacting with the environmental situation. A set of real-time video images are received that are captured by at least one video camera associated with an environment presenting one or more environmental situations to a human. One or more user actions made by the human that is associated with the set of real-time video images with respect to the environmental situation are monitored. A determination is made, based on the monitoring, that the human driver has one of performed and failed to perform at least one action associated with one or more images of the set of real-time video images. The one or more images of the set of real-time video images are annotated with a set of annotations.

Abstract: Techniques for classifying one or more objects in at least one video, wherein the at least one video comprises a plurality of frames are provided. One or more objects in the plurality of frames are tracked. A level of deformation is computed for each of the one or more tracked objects in accordance with at least one change in a plurality of histograms of oriented gradients for a corresponding tracked object. Each of the one or more tracked objects is classified in accordance with the computed level of deformation.

Abstract: A solution for monitoring an area uses color histograms and size information (e.g., heights and widths) for blob(s) identified in an image of the area and model(s) for existing object track(s) for the area. Correspondence(s) between the blob(s) and the object track(s) are determined using the color histograms and size information. Information on an object track is updated based on the type of correspondence(s). The solution can process merges, splits and occlusions of foreground objects as well as temporal and spatial fragmentations.

Abstract: A person detection system includes a face detector configured to detect a face in an input video sequence, the face detector outputting a face keyframe to be stored if a face is detected; and a person detector configured to detect a person in the input video sequence if the face detector fails to detect a face, the person detector outputting a person keyframe to be stored, if a person is detected in the input video sequence.