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. 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. A status of a static object is determined as either an abandoned status if the static object is an abandoned object or a removed status if the static object is a removed object.

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. A determination is made that a persistence requirement, a non-persistence duration requirement, and a persistence duration requirement have been satisfied.

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: An approach that detects locations of hazardous conditions within an infrastructure is provided. This approach uses satellite imagery, GIS data, automatic image processing, and predictive modeling to determine the location of the hazards automatically, thus optimizing infrastructure management. Specifically, a hazard detection tool provides this capability. The hazard detection tool comprises a detection component configured to: receive visual media containing asset location data about a set of physical assets, and hazard location data about potential hazards within a vicinity of each of the set of physical assets. The detection component further receives graphical information system (GIS) data containing asset location data about each of the set of physical assets.

Abstract: An approach that evaluates an effectiveness of a monitoring system is provided. In one embodiment, there is a performance evaluation tool, including an evaluation component configured to receive visual media at a monitoring system monitored by a set of users, and evaluate a monitoring performance of the set of users in response to a simulated alert within the visual media. The performance evaluation tool further comprises an analysis component configured to predict an effectiveness of the monitoring system based on the performance of the set of users in response to the simulated alert within the visual media.

Abstract: An approach that detects locations of hazardous conditions within an infrastructure is provided. This approach uses satellite imagery, GIS data, automatic image processing, and predictive modeling to determine the location of the hazards automatically, thus optimizing infrastructure management. Specifically, a hazard detection tool provides this capability. The hazard detection tool comprises a detection component configured to: receive visual media containing asset location data about a set of physical assets, and hazard location data about potential hazards within a vicinity of each of the set of physical assets. The detection component further receives graphical information system (GIS) data containing asset location data about each of the set of physical assets.

Abstract: Embodiments relate analytic solution integration. According to an aspect, a method for analytic solution integration includes establishing an engine abstraction layer configured to interface with a plurality of analytic engines associated with a plurality of models. A services layer is interfaced with the engine abstraction layer to provide a communication interface to invoke the analytic engines associated with the models. A user interface is provided to the services layer. The user interface is configured to define an analytic solution as an executable sequence of one or more of the models.

Abstract: A system and computer program product for performing visual surveillance of one or more moving objects 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: Embodiments relate analytic solution integration. According to an aspect, a method for analytic solution integration includes establishing an engine abstraction layer configured to interface with a plurality of analytic engines associated with a plurality of models. A services layer is interfaced with the engine abstraction layer to provide a communication interface to invoke the analytic engines associated with the models. A user interface is provided to the services layer. The user interface is configured to define an analytic solution as an executable sequence of one or more of the models.

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: An invention for identifying a spatial location of an event within video image data is provided. Disclosed are embodiments for detecting an object and obtaining trajectory data of a trajectory of the object within the video image data from a sensor device; converting the trajectory data into a contour-coded compressed image; generating, based on the trajectory data, a searchable code that contains a set of locations traversed by the trajectory of the object within the video image; associating the searchable code with the contour-coded compressed image in a database; and returning, in response to a query having a selected location that corresponds a location of the set of locations in the searchable code, an image of the trajectory data corresponding to the object based on the contour-coded compressed image in the database.

Abstract: Under the present invention, item verification is automated and expedited. Specifically, items to be purchased can be scanned by the shopper using a barcode reader (e.g., a scanner), attached to or positioned near the checkout station. As items are scanned, they are identified based on their barcode, and added to an item list. Item verification can then be performed at checkout using imaging technology. Specifically, as items are scanned, an item verification unit will capture an appearance thereof (via a camera). Item verification software within the item verification unit will access a database that associates items with their images/appearances. The appearance will be compared for consistency to the identity as determined based on the scan. In general, the item verification unit is a separate unit from the cash register, but adapted to work in conjunction therewith (e.g., as a pluggable system, via wireless communication, etc.).

Abstract: Embodiments relate to traffic impact prediction in a transportation network. Link level background traffic demand in a transportation network may be estimated based on information about available routes, and based on expected background traffic volumes between origins and destinations. A background traffic flow model that optimizes a background flow of the expected background traffic volumes among the available routes to minimize a sum of background congestion costs, background path entropy, and errors between an observed background traffic flow and the optimized background flow may be applied. Alternative routes may be identified based on the available routes and event based control plans. Expected additional event based traffic volumes may be received. A link level total traffic demand in the transportation network may be estimated based on the expected additional event based traffic volumes, the identified alternative routes, and the estimated background traffic demand.

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 derived from a video input, wherein each version has a different resolution of said image of said object; computing an appearance score at each of a plurality of regions on the lowest resolution version of said plurality of versions of said image for at least one attribute for said object, wherein said appearance score denotes a probability of the at least one attribute appearing in the region; determining a configuration of the at least one attribute in the lowest resolution version based on at least the appearance score in each of the plurality of regions in the lowest resolution version; and displaying said configuration.

Abstract: A system comprises an input component, a feature extractor, an object classifier, an adaptation component and a calibration tool. The input component is configured to receive one or more images, and the feature extractor is configured to extract features for one or more objects in the one or more images, the extracted features comprising at least one view-independent feature. The object classifier is configured to classify the one or more objects based at least in part on the extracted features and one or more object classification parameters, and the adaptation component is configured to adjust the classification of at least one of the objects based on one or more contextual parameters. The calibration tool is configured to adjust one or more of the object classification parameters based on likelihoods for characteristics associated with one or more object classes.

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 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, 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: Embodiments relate to analytics driven assessment of transactional risk daily limit (TRDL) exceptions. A transaction that includes a request to make a payment from an account associated with a customer is received and it is determined that processing the payment will result in exceeding a TRDL. Customer data including historical transaction data and customer profile data associated with the customer is accessed by a processor. Economic data from an external data source is accessed via a network from an external data source. A TRDL exception assessment model is applied, by the processor, to the transaction, the customer data, and the economic data to generate an approval recommendation for the request and a confidence level associated with the approval recommendation.

Abstract: An aspect of product pricing includes classifying customers into groups based on shared, predefined characteristics and financial transactions, and identifying services rendered and available but not rendered. For each customer, a risk associated with a service is estimated; availability and prices of the service by third parties are determined; a price for the service set by the entity is compared with the prices set by the third parties; and a demand for the service of the entity is estimated as a function of the availability and prices of the service by the third parties. For each customer, a probability that the customer will purchase the service is estimated based on the demand, and a price for the service that is customized for the customer is calculated, as a function of the risk, the demand, and the probability of purchase, and in view of a target profit and/or target revenue.

Abstract: Embodiments relate to a transactional risk daily limit (TRDL) update alarm. Customer data including historical transaction data and customer profile data is accessed, along with economic data from an external data source. A TRDL alarm analytics model is applied to the customer data and the economic data to predict a number of transactions in a specified time period that are expected to exceed a TRDL. The TRDL alarm analytics model takes into account a payment transaction pattern associated with the customer. A threshold value is compared to the number of transactions in the specified time period that are expected to exceed the TRDL. An increase in the TRDL is requested to be applied at least during the specified time period based on the number of transactions in the specified time period that are expected to exceed the TRDL being greater than the threshold value.

Abstract: An aspect of customer selection processes includes classifying, by a computer processor, customers of an entity into groups based on commonly shared, predefined characteristics among the customers. For each of the groups: services rendered for corresponding customers are identified; for each of the services rendered, a risk relationship and a reward relationship between each of the corresponding customers and the service is determined; and for each of the services rendered, a score that defines a combination of the risk relationship and the reward relationship is calculated. For each of the services rendered by the entity, the corresponding score is applied to a candidate customer having a set of characteristics matching the characteristics of one of the groups, and the service is offered to the candidate customer as a function of the score.