Abstract: A global position of an observed object is determined by obtaining a first global position of an observed object with at least one positioning device. A determination is made as to whether a set of stored visual characteristic information of at least one landmark matches a visual characteristic information set obtained from at least one captured image comprising a scene associated with the observed object. In response to the set of stored visual characteristic information matching the obtained visual characteristic information set, a second global position of the observed object is determined based on a set of stored location information associated with the at least one landmark and the first global position.

Abstract: A method, system, and computer program product for automatically inspecting railroad tracks. The method includes assessing a configuration of rail components depicted in an image by comparing the configuration of the rail components to known hazards. The method also includes determining a severity of detected problems in the configuration of the rail components, using a computer processor.

Abstract: Video image data is acquired from synchronized cameras having overlapping views of objects moving past the cameras through a scene image in a linear array and with a determined speed. Processing units generate one or more object detections associated with confidence scores within frames of the camera video stream data. The confidence scores are modified as a function of constraint contexts including a cross-frame constraint that is defined by other confidence scores of other object detection decisions from the video data that are acquired by the same camera at different times; a cross-view constraint defined by other confidence scores of other object detections in the video data from another camera with an overlapping field-of-view; and a cross-object constraint defined by a sequential context of a linear array of the objects, spatial attributes of the objects and the determined speed of the movement of the objects relative to the cameras.

Abstract: A method, data processing system, and computer program product for managing a headlight on a vehicle are presented. An image of an area in front of the vehicle is received. A first set of features is identified in the received image. The first set of features in the received image is compared with a number of sets of features from a plurality of previous images. Each image in the plurality of previous images is associated with a headlight setting. A second set of features from a previous image in the plurality of previous images matching the first set of features in the received image is identified. A determination is made whether to change a setting for the headlight on the vehicle based on the headlight setting associated with the previous image.

Abstract: Techniques for segmenting an object at a self-checkout are provided. The techniques include capturing an image of an object at a self-checkout, dividing the image into one or more blocks, computing a confidence value for each of the one or more blocks, and eliminating one or more blocks from consideration based on the confidence value for each of the one or more blocks, wherein the one or more blocks remaining map to a region of the image containing the object.

Abstract: Techniques are provided. The techniques include capturing an image of an object at a self-checkout, dividing the image into one or more blocks, computing one or more features of the image, computing a confidence value for each of the one or more blocks, wherein computing a confidence value for each of the one or more blocks comprises using a minimum feature distance from one or more reference background blocks, and eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks, wherein the one or more blocks remaining map to a region of the image containing the object.

Abstract: An imaging system includes an image capturing device and a plurality of reflective devices. The image capturing device is configured to receive a plurality of images reflected by the plurality of reflective devices. Responsive to receiving the plurality of images, the image capturing device is further configured to capture within a single frame at least a first image corresponding to a first side of a first railroad track rail, a second image corresponding to a second side of the first railroad track rail, a third image corresponding to a first side of a second railroad track rail, and a fourth image corresponding to a second side of the second railroad track rail.

Abstract: A system, method, and computer program product for detecting anomalies in an image. In an example embodiment the method includes partitioning each image of a set of images into a plurality of image local units. The method further includes clustering all local units in the image set into clusters, and consequently assigning a class label to each local unit based on the clustering results. The local units with identical class labels having at least one substantially related image feature. Further, the method includes assigning a weight to each of the local units based on a variation of the class labels across all images in a set of images. The method further includes performing a clustering over all images in the set by using a distance metric that takes the learned weight of each local unit into account, then determining the images that belong to minorities of the clusters as anomalies.

Abstract: A computer implemented method, a computer program product, and data processing system clone virtual machines in a virtual desktop environment. A request to clone a new virtual machine is intercepted, wherein the request was initially sent to a virtual management server. Responsive to intercepting the request, the new virtual machine is cloned from a snapshot of a master virtual machine. A delta file is created for the new virtual machine, wherein the delta file includes a base disk reference and a copied delta file. The new virtual machine is configured to read a base disk image from a snapshot of the master virtual machine. The new virtual machine is configured to write data to the copied delta file in the delta file.

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: A method, data processing system, and computer program product for identifying abnormalities in data. A model representing a plurality of modes for an activity generated from training data is retrieved. The training data includes a first plurality of measurements of a first performance of the activity over a period of time. Each of the plurality of modes is identified as one of normal and abnormal. Activity data including a second plurality of measurements of a second performance of the activity is received. A portion of the activity data is compared with the plurality of modes in the model. A notification of an abnormality in the second performance of the activity is generated in response to an identification that the portion of the activity data matches a mode in the plurality of modes identified as abnormal. Confirmation of the abnormality is requested via a user interface.

Abstract: A method, system, and computer program product for automatically inspecting railroad tracks. The method includes assessing a configuration of rail components depicted in an image by comparing the configuration of the rail components to known hazards. The method also includes determining a severity of detected problems in the configuration of the rail components, using a computer processor.

Abstract: A method, data processing system, and computer program product for managing a headlight on a vehicle are presented. An image of an area in front of the vehicle is received. A first set of features is identified in the received image. The first set of features in the received image is compared with a number of sets of features from a plurality of previous images. Each image in the plurality of previous images is associated with a headlight setting. A second set of features from a previous image in the plurality of previous images matching the first set of features in the received image is identified. A determination is made whether to change a setting for the headlight on the vehicle based on the headlight setting associated with the previous image.

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 segmenting an object at a self-checkout are provided. The techniques include capturing an image of an object at a self-checkout, dividing the image into one or more blocks, computing one or more features of the image, computing a confidence value for each of the one or more blocks, wherein computing a confidence value for each of the one or more blocks comprises using a minimum feature distance from one or more reference backgound blocks, and eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks, wherein the one or more blocks remaining map to a region of the image containing the object.

Abstract: The present invention provides a solution for controlling checkout throughput. Specifically, under the present invention a set of attributes of an item will be obtained. An analysis of the set of attributes will then be performed to determine whether an inconsistency exists based on a tolerance threshold. Such analysis can include, for example, comparing the weight of the item to its expected weight. This can help determine if a mistake has been made or fraud has been committed. Whether an inconsistency is observed is based on a tolerance threshold. For example, a certain deviation (i.e., the tolerance threshold) from an expected value could be allowed to could be allowed to reduce errors during the checkout process and thereby increase checkout throughput. As such, the present invention allows the tolerance threshold to be tuned based on a desired checkout throughput.

Abstract: A computer implemented method, a computer program product, and data processing system clone virtual machines in a virtual desktop environment. A request to clone a new virtual machine is intercepted, wherein the request was initially sent to a virtual management server. Responsive to intercepting the request, the new virtual machine is cloned from a snapshot of a master virtual machine. A delta file is created for the new virtual machine, wherein the delta file includes a base disk reference and a copied delta file. The new virtual machine is configured to read a base disk image from a snapshot of the master virtual machine. The new virtual machine is configured to write data to the copied delta file in the delta file.

Abstract: The present invention provides a solution for controlling checkout throughput. Specifically, under the present invention a set of attributes of an item will be obtained. An analysis of the set of attributes will then be performed to determine whether an inconsistency exists based on a tolerance threshold. Such analysis can include, for example, comparing the weight of the item to its expected weight. This can help determine if a mistake has been made or fraud has been committed. Whether an inconsistency is observed is based on a tolerance threshold. For example, a certain deviation (i.e., the tolerance threshold) from an expected value could be allowed to could be allowed to reduce errors during the checkout process and thereby increase checkout throughput. As such, the present invention allows the tolerance threshold to be tuned based on a desired checkout throughput.

Abstract: A non-scan detect system for a retail checkout station includes a non-scan detect module. The non-scan detect module, when operated, causes the non-scan detect system to detect the passing of an item across a scanner device of a retail checkout station, determine that the item passing across the scanner device was not registered as a scan, establish a potential non-scanned item based on the item not being registered as a scan, obtain an image of the potential non-scanned item, establish a scanned item based on an item passing across the scanner device being registered as a scan, extract features associated with the scanned item, compare the features associated with the scanned item with the image of the potential non-scanned item, and trigger an actual non-scan if the features of the scanned item do not substantially match the image of the potential non-scanned item.

Abstract: A method for detecting a non-scan at a retail checkout station includes detecting the passing of an item across a scanner device of a retail checkout station, obtaining an image of the item passing across the scanner, detecting a scan of an item passing across the scanner to establish a scanned item, and establishing a register associated with the scanned item. A scan occurs if the image of the item passing across the scanner substantially matches the register associated with the scanned item. Conversely, a non-scan is triggered when the image of the item passing across the scanner does not match the register associated with the scanned item.