Abstract: Embodiments relate to generating a trajectory heat map at an aggregated level using computed transit points is provided. An aspect includes generating, by a processing device, a trajectory database from time-stamped global positioning system (GPS) sample points. According to exemplary embodiments, transit points are computed for each trajectory in the trajectory database. A temporal transit graph is constructed from the transit points. The transit graph of embodiments captures the shortest paths among these transit points. The transit graph is then indexed and stored in a spatial-temporal database for online analytic processing.

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: 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: A system and computer program product for tracking and monitoring assets along a transport route. The system includes at least one receiver for receiving asset identifications transmitted from the assets, where each asset transmits its own asset identification. The receiver also receives physical location coordinates of each of the assets. A plurality of cameras is dispersed along the transport route for transmitting camera images of the assets. The system further includes a server coupled to the receiver and cameras. The server is configured to recognize the assets in the camera images, to correlate the asset identification from the receiver with recognized assets in the camera images, and to correlate the physical location coordinates of each of the assets with physical location coordinates of the cameras. The system monitors the visual appearance of the assets, and keeps track of whether or not they have sustained physical damage.

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: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.

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: An approach for generating a coding schema for identifying a spatial location of an event within video image data is provided. In one embodiment, there is a spatial representation tool, including a compression component configured to receive trajectory data of a trajectory of an object for an event within video image data; generate a lossless compressed contour-coded blob to encode the trajectory data of the trajectory of the object for the event within video image data; generate a lossy searchable code of the trajectory of the object for the event within the video image data; convert a region of interest within the video image data to a lossy query code, the region of interest corresponding to a sub-section of a visual display output of the video image data; and compare the lossy query code to the lossy searchable code within a relational database to identify a corresponding lossless trajectory data of the trajectory of the object for the event within the video image data.

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: 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: 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: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.

Abstract: Multi-mode video event indexing includes determining a quality of object distinctiveness with respect to images from a video stream input. A high-quality analytic mode is selected from multiple modes and applied to video input images via a hardware device to determine object activity within the video input images if the determined level of detected quality of object distinctiveness meets a threshold level of quality, else a low-quality analytic mode is selected and applied to the video input images via a hardware device to determine object activity within the video input images, wherein the low-quality analytic mode is different from the high-quality analytic mode.

Abstract: Human behavior alerts are determined from a video stream through application of video analytics that parse a video stream into a plurality of segments, wherein each of the segments are either temporally related to at least one of a plurality of temporally distinct transactions in an event data log; or they are each associated with a pseudo transaction marker if not temporally related to at least one of the temporally distinct transactions and an image analysis indicates a temporal correlation with at least one of the distinct transactions is expected. Visual image features are extracted from the segments and one-SVM classification is performed on the extracted features to categorize segments into inliers or outliers relative to a threshold boundary. Event of concern alerts are issued with respect to the inlier segments associated with the associated pseudo transaction marker.

Abstract: Techniques for creating a training technique for an individual are provided. The techniques include obtaining video of one or more events and information from a transaction log that corresponds to the one or more events, wherein the one or more events relate to one or more actions of an individual, classifying the one or more events into one or more event categories, comparing the one or more classified events with an enterprise best practices model to determine a degree of compliance, examining the one or more classified events to correct one or more misclassifications, if any, and revise the one or more event categories with the one or more corrected misclassifications, if any, and using the degree of compliance to create a training technique for the individual.

Abstract: Multiple event types are monitored for events, and surveillance data is stored for each event. Surveillance data for a primary event of one event type can be presented to a user, and surveillance data for a set of related events corresponding to another event type can be presented based on a set of relatedness criteria and the surveillance data for the primary event. A user can adjust the relatedness criteria to filter/adjust the surveillance data presented for the related event(s). A user interface can enable the user to simultaneously view the surveillance data for both events and adjust the relatedness criteria. In an illustrative application, the invention is utilized to detect fraudulent merchandise returns in a retail store.

Abstract: Methods, systems, and computer program products for parsing objects in a video are provided herein. A method includes producing a plurality of versions of an image of an object, wherein each version has a different resolution of said image of said object, and computing an appearance score at each of a plurality of regions on the lowest resolution version for at least one semantic attribute for said object. Such a method also includes analyzing one or more other versions to compute a resolution context score for each of the plurality of regions in the lowest resolution version, wherein said resolution context score denotes an extent to which finer spatial structure exists in the one or more others versions than in the lowest resolution version, and determining a configuration of the at least one semantic attribute in the lowest resolution version based on the appearance score and the resolution context score.

Abstract: Techniques, systems, and computer program products for parsing objects in a video are provided herein. A method includes producing and storing a plurality of versions of an image of an object derived from a video input, wherein each version of said image has a different resolution of said image; computing an appearance score at each of a plurality of regions on the lowest resolution version of said image for a plurality of semantic attributes with associated parts for said object, said appearance score denoting a probability of each semantic attribute appearing in the region; analyzing increasingly higher resolution versions than the lowest resolution version to compute a resolution context score for each region in the lowest resolution version; and ascertaining an optimized configuration of body parts and associated semantic attributes in the lowest resolution version, said ascertaining utilizing the appearance scores and the resolution context scores.

Abstract: Determination of human behavior from an alignment of data streams includes acquiring visual image primitives from a video input comprising visual information relevant to a human activity. The primitives are temporally aligned to an optimally hypothesized sequence of primitives transformed from a sequence of transactions as a function of a distance metric between the observed primitive sequence and the transformed primitive sequence. More particularly, transforming includes comparing the distance metric costs and choosing and performing the lowest cost of temporally matching the observed primitives to one or more transactions, deleting a primitive, or associating a primitive with a pseudo transaction marker. Accordingly, alerts are issued based on analysis of the transformation of primitives.

Abstract: A system and method that processes video to extract a keyframe-based adequate visual representation is disclosed. Certain embodiments utilize a hierarchical processing technique. A first stage in the hierarchy extracts a chromatic difference metric from a pair of video frames. An initial set of frames is chosen based on the chromatic metric and a threshold. A structural difference measurement is extracted from this initial set of frames. A second threshold is used to select key frames from the initial set. The first and second thresholds can be user selectable. The output of this process is the visual representation. The method is extensible to any number of metrics and any number of levels.