Abstract: A method of calibrating a system including a camera, the method including detecting a robot navigating within an environment modeled as a geo-polygon space, including a transit of the robot through a scene of the environment captured by the camera, mapping a plurality of points occupied by the robot in images of the scene to the geo-polygon space, recording data about the mapping, and configuring at least one alert using the data recorded about the mapping, the alert executed by the computing system and configured to be triggered by an object transiting the scene.

Abstract: Aspects of this disclosure relate to a system that uses images of a load handled by a crane as captured by cameras to monitor the load. The images may include different sets of outer perimeters of the load. The system may identify the outer perimeters and then define a safety zone that extends beyond these outer perimeters. In response to identifying an object within the safety zone, the system may execute a remedial action.

Abstract: A method, system, and computer program product for automated collection of training data and training object detection models is provided. The method generates a set of reference images for a first set of products. Based on the set of reference images, the method identifies a subset of products within an image stream. Based on the subset of products, a second set of products is determined within the image stream. The method identifies a set of product gaps based on the subset of products and the second set of products. The method generates a product detection model based on the set of reference images, the subset of products, the second set of products, and the product gaps.

Abstract: Selectively redacting an image by determining a set of attributes used by a machine learning model for an analysis, receiving image data detecting, by the one or more computer processors, a portion of the image data relevant to the analysis, the portion comprising at least some of the set of attributes, generating a synthetic portion from the portion, wherein the synthetic portion retains at least some of the attributes of the detected portion, replacing the portion with the synthetic portion, yielding redacted image data, and providing the redacted image data for analysis.

Abstract: A method of calibrating a system including a camera, the method including detecting a robot navigating within an environment modeled as a geo-polygon space, including a transit of the robot through a scene of the environment captured by the camera, mapping a plurality of points occupied by the robot in images of the scene to the geo-polygon space, recording data about the mapping, and configuring at least one alert using the data recorded about the mapping, the alert executed by the computing system and configured to be triggered by an object transiting the scene.

Abstract: Selectively redacting an image by determining a set of attributes used by a machine learning model for an analysis, receiving image data detecting, by the one or more computer processors, a portion of the image data relevant to the analysis, the portion comprising at least some of the set of attributes, generating a synthetic portion from the portion, wherein the synthetic portion retains at least some of the attributes of the detected portion, replacing the portion with the synthetic portion, yielding redacted image data, and providing the redacted image data for analysis.

Abstract: In an approach for efficient data processing in a mesh network of computing devices, a processor receives data to be processed in the mesh network. A processor distributes a set of computational units to a set of computing devices in the mesh network. A processor creates a computational plan to construct a computational pipeline of the set of computational units. The computational plan considers cost and performance trade-offs by considering limitation of hardware resources, processing speed, accuracy and application requirements. A processor executes the computational plan by sending data to assigned computational units.

Abstract: Provided are techniques for optimized deployment of analytic models in an edge topology. A description of a multi-tiered edge topology with a plurality of nodes, a multimedia stream analytics composition, and performance objectives are received, where the multimedia stream analytics composition includes tasks that use analytic models. The analytic models are optimized and clustered to form clusters of optimized analytic models. A representative optimized analytic model is selected from each of the clusters. A configuration recommendation is determined that indicates deployment of the tasks and of each selected representative optimized analytic model on the plurality of nodes to meet the performance objectives. One or more workflows are generated from the configuration recommendation and executed on the plurality of nodes to generate output for the multimedia stream analytics composition.

Abstract: A method, system, and computer program product for automated collection of training data and training object detection models is provided. The method generates a set of reference images for a first set of products. Based on the set of reference images, the method identifies a subset of products within an image stream. Based on the subset of products, a second set of products is determined within the image stream. The method identifies a set of product gaps based on the subset of products and the second set of products. The method generates a product detection model based on the set of reference images, the subset of products, the second set of products, and the product gaps.

Abstract: In an approach for efficient data processing in a mesh network of computing devices, a processor receives data to be processed in the mesh network. A processor distributes a set of computational units to a set of computing devices in the mesh network. A processor creates a computational plan to construct a computational pipeline of the set of computational units. The computational plan considers cost and performance trade-offs by considering limitation of hardware resources, processing speed, accuracy and application requirements. A processor executes the computational plan by sending data to assigned computational units.

Abstract: Provided are techniques for optimized deployment of analytic models in an edge topology. A description of a multi-tiered edge topology with a plurality of nodes, a multimedia stream analytics composition, and performance objectives are received, where the multimedia stream analytics composition includes tasks that use analytic models. The analytic models are optimized and clustered to form clusters of optimized analytic models. A representative optimized analytic model is selected from each of the clusters. A configuration recommendation is determined that indicates deployment of the tasks and of each selected representative optimized analytic model on the plurality of nodes to meet the performance objectives. One or more workflows are generated from the configuration recommendation and executed on the plurality of nodes to generate output for the multimedia stream analytics composition.

Abstract: Aspects of this disclosure relate to a system that uses images of a load handled by a crane as captured by cameras to monitor the load. The images may include different sets of outer perimeters of the load. The system may identify the outer perimeters and then define a safety zone that extends beyond these outer perimeters. In response to identifying an object within the safety zone, the system may execute a remedial action.

Abstract: A computer-implemented method for assigning one or more conveyor belts to convey a plurality of items. The computer-implemented method determines an availability of one or more conveyor belts, determines a quantity of a plurality of items to be loaded onto the one or more conveyor belts, and assigns the one or more conveyor belts to convey the plurality of items, based on the determined quantity of the plurality of items to be loaded onto the one or more conveyor belts. The computer-implemented method further tracks a location of each of the plurality of items on the assigned one or more conveyor belts, associates each of the plurality of items with a user, and directs the user to the one or more conveyor belts based on the tracked location of each of the plurality of items associated with the user.

Abstract: A computer-implemented method for assigning one or more conveyor belts to convey a plurality of items. The computer-implemented method determines an availability of one or more conveyor belts, determines a quantity of a plurality of items to be loaded onto the one or more conveyor belts, and assigns the one or more conveyor belts to convey the plurality of items, based on the determined quantity of the plurality of items to be loaded onto the one or more conveyor belts. The computer-implemented method further tracks a location of each of the plurality of items on the assigned one or more conveyor belts, associates each of the plurality of items with a user, and directs the user to the one or more conveyor belts based on the tracked location of each of the plurality of items associated with the user.

Abstract: Techniques for detecting one or more events are provided. The techniques include identifying one or more segments in a video sequence as one or more candidates for one or more events by a temporal ordering of the one or more candidates, and analyzing one or more motion patterns of the one or more candidates to detect the one or more events.

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 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 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: 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: 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.