Abstract: A method, system and computer program product for detecting anomalies in a metering system. In one embodiment, data representing usage of a defined commodity are collected from meters, and the data collected over a given time period are analyzed to identify any of the meters showing at least one defined type of anomalous usage pattern. For each of the meters showing an anomalous usage patterns, an anomaly score is determined for the usage pattern shown, and the anomaly scores are used to rank the meters. In one embodiment, the collected data are analyzed to identify any of the meters showing one or more of a group of types of anomalous patterns including meter-no-reading, meter-by-pass, and meter-silting patterns. Embodiments of the invention utilize time series techniques and data analysis on meter reading data. Further, embodiments of the invention require no additional installation of equipment or sensors.

Abstract: An invention 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 an event within video image data, generate a lossless compressed contour-coded blob to encode the trajectory data of the event within video image data, and generate a lossy searchable code to enable searching of a relational database based on the trajectory data of the event within the video image data.

Abstract: An invention for identifying a spatial location of an event within video image data is provided. Disclosed are embodiments for generating trajectory data of a trajectory of an object for a plurality of pixel regions of an area of interest within video image data, the generating comprising: identifying one or more pixel regions from the plurality of pixel regions containing trajectory data; performing a multi-point neighborhood scan within the one or more pixel regions from the plurality of pixel regions containing trajectory data; and generating a transition chain code based on the multi-point neighborhood scan. Embodiments further generate a set of compressed spatial representations of the trajectory data of the trajectory of the object for an event based on the transition chain code, and generate a lossless contour code of the trajectory data of the trajectory of the object for the event based on the transition chain code.

Abstract: The present invention provides an item scanning system in which an appearance of an item is received (e.g., at checkout). The appearance is captured with an image capture device (e.g., still frame camera, video camera, etc.) that can be collocated with a barcode scanner. In being collocated, the image capture device can be positioned proximate (e.g., near, attached to, etc.) the bar code scanner, integrated within a common housing/unit with the barcode scanner, etc. In any event, a search engine will then search a database of items based on the appearance to identify a set of items that potentially match the item. When one of the set of items is selected (e.g., by the checkout clerk), the selection will be received and stored for future investigation/auditing.

Abstract: Techniques for calibrating a classification system, wherein one or more objects in at least one video are classified, are provided. At least one view associated with the at least one video is obtained. The at least one view is partitioned into at least one region. A given object is classified in accordance with its location in reference to the at least one region. In an additional embodiment, one or more object models are obtained. At least one normalized size of the one or more objects is defined within at least one view associated with the at least one video in accordance with the one or more object models. The one or more objects are classified in accordance with the at least one defined normalized size.

Abstract: Techniques for performing foreground analysis are provided. The techniques include identifying a region of interest in a video scene, detecting a static foreground object in the region of interest, and determining whether the static foreground object is abandoned or removed, wherein said determining comprises performing a foreground analysis based on tracking information and pruning one or more false alarms using one or more track statistics.

Abstract: Techniques, systems, and articles of manufacture for multispectral detection of attributes for video surveillance. A method includes generating one or more training sets of one or more multispectral images, generating a group of one or more multispectral box features, using the one or more training sets to select one or more of the one or more multispectral box features to generate a multispectral attribute detector, and using the multispectral attribute detector to identify a location of an attribute in video surveillance, wherein using the multispectral attribute detector comprises, for one or more locations on each spectral band level of the multispectral image, applying the multispectral attribute detector and producing an output indicating attribute detection or an output indicating no attribute detection, and wherein the attribute corresponds to the multispectral attribute detector.

Abstract: An invention 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 an event within video image data, and generate a set of compressed spatial representation of the trajectory data of the event within the video image data. A database component is configured to input the set of compressed spatial representations into a relational database, and a search component is configured to search the relational database to identify a spatial location of the event within the video image data.

Abstract: The invention provides an improved method to detect semantic attributes of human body in computer vision. In detecting semantic attributes of human body in computer vision, the invention maintains a list of semantic attributes, each of which corresponds to a human body part. A computer module then analyzes segments of a frame of a digital video to detect each semantic attribute by finding a most likely attribute for each segment. A threshold is applied to select candidate segments of the frame for further analysis. The candidate segments of the frame then go through geometric and resolution context analysis by applying the physical structure principles of a human body and by analyzing increasingly higher resolution versions of the image to verify the existence and accuracy of parts and attributes.

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: 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: Techniques for detecting an attribute in video surveillance include generating training sets of multispectral images, generating a group of multispectral box features comprising receiving input of a detector size of a width and height, a number of spectral bands in the multispectral images, and integer values representing a minimum and maximum width and height of multispectral box features, fixing a feature width and height, generating feature building blocks with the fixed width and height, placing a feature building block at a same location for each spectral band level, and enumerating combinations of the feature building blocks through each spectral level until all sizes within the integer values have been covered, and wherein each combination determines a multispectral box feature, using the training sets to select multispectral box features to generate a multispectral attribute detector, and using the multispectral attribute detector to identify a location of an attribute in video surveillance.

Abstract: An approach that dynamically learns a set of attributes of an operator of a point of sale (POS) is provided. In one embodiment, there is an attribute tool, including an extraction component configured to receive sensor data of a set of moving objects, and extract a set of attributes from each of the set of moving objects captured within the scan area at the POS; an identification component configured to update an appearance model with the set of attributes from each of the set of moving objects; and an analysis component configured to analyze the appearance model to identify at least one of the set of moving objects as an operator of the POS.

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: There is provided an apparatus for the certification of privacy compliance. The apparatus includes a registry of at least one of enrolled video surveillance operators, approved surveillance hardware devices, approved surveillance software programs, approved surveillance system installers, and approved entities that manage surveillance systems. The apparatus further includes a registry searcher, in signal communication with the registry, for receiving queries to the registry, and for determining whether at least one of a particular surveillance operator, a particular surveillance hardware device, a particular surveillance software program, a particular surveillance system installer, and a particular entity that manages a particular surveillance system is on the registry based on a given query.

Abstract: Techniques are provided. The techniques include identifying a region of interest in a video scene, applying a background subtraction algorithm to the region of interest to detect a static foreground object in the region of interest, and determining whether the static foreground object is abandoned or removed, wherein determining whether the static foreground object is abandoned or removed comprises performing a foreground analysis based on edge energy and region growing, and pruning one or more false alarms using one or more track statistics.

Abstract: Techniques for calibrating a classification system, wherein one or more objects in at least one video are classified, are provided. At least one view associated with the at least one video is obtained. The at least one view is partitioned into at least one region. A given object is classified in accordance with its location in reference to the at least one region. In an additional embodiment, one or more object models are obtained. At least one normalized size of the one or more objects is defined within at least one view associated with the at least one video in accordance with the one or more object models. The one or more objects are classified in accordance with the at least one defined normalized size.

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 generating an alert based on absence of a given person in a transaction are provided. The techniques include monitoring, via video, a transaction, wherein the transaction includes presence of a given person in the transaction, relating the video of the transaction to a corresponding portion of a transaction log (TLOG), using the video and corresponding portion of the TLOG to detect if the given person in the transaction is present, and generating an alert if the given person is not present at the transaction.

Abstract: A system, method and computer program product for maintaining an infrastructure of components. The system receives structured data, unstructured data, and infrastructure data from a database. The system runs at least one statistical and optimization modeler with one or more of: the received structured data, the received unstructured data and the received infrastructure data, in order to calculate a health index of at least one component of the infrastructure. The health index represents a health attribute of the at least one component. The system establishes at least one maintenance plan of the infrastructure, based on the calculated health index. Each established maintenance plan is associated with at least one health index. The system compares health indices of the at least one established maintenance plan. The system selects a plan, among the at least one established maintenance plan, whose health index is a maximum among the compared health indices.