Abstract: Combined color and depth data for a field of view is received. Thereafter, using at least one bounding polygon algorithm, at least one proposed bounding polygon is defined for the field of view. It can then be determined, using a binary classifier having at least one machine learning model trained using a plurality of images of known objects, whether each proposed bounding polygon encapsulates an object. The image data within each bounding polygon that is determined to encapsulate an object can then be provided to a first object classifier having at least one machine learning model trained using a plurality of images of known objects, to classify the object encapsulated within the respective bounding polygon.

Abstract: RGB-D data generated by at least one optical sensor for a field of view is received. Thereafter, the RGB-D data is bifurcated into (i) RGB data and (ii) depth data for the field of view. One or more bounding polygons are defined within the depth data that each characterize a window within the field of view encapsulating an object. The RGB data is then cropped using the bounding polygon(s). Image processing can later be applied to the cropped RGB data to identify at least one object therein. Related apparatus, systems, techniques and articles are also described.

Abstract: Image color data for a field of view is received. Thereafter, color segmentation can be performed on the image color data to define at least one bounding polygon that minimizes an amount of free space within each bounding polygon. The at least one bounding polygon is then used to crop the image color data to result in cropped image color data. Image processing can then be applied to the cropped image color data to identify at least one object therein. Related apparatus, systems, techniques and articles are also described.

Abstract: Combined color and depth data for a field of view is received. Thereafter, using at least one bounding polygon algorithm, at least one proposed bounding polygon is defined for the field of view. It can then be determined, using a binary classifier having at least one machine learning model trained using a plurality of images of known objects, whether each proposed bounding polygon encapsulates an object. The image data within each bounding polygon that is determined to encapsulate an object can then be provided to a first object classifier having at least one machine learning model trained using a plurality of images of known objects, to classify the object encapsulated within the respective bounding polygon.

Abstract: RGB-D data generated by at least one optical sensor for a field of view is received. Thereafter, the RGB-D data is bifurcated into (i) RGB data and (ii) depth data for the field of view. One or more bounding polygons are defined within the depth data that each characterize a window within the field of view encapsulating an object. The RGB data is then cropped using the bounding polygon(s). Image processing can later be applied to the cropped RGB data to identify at least one object therein. Related apparatus, systems, techniques and articles are also described.

Abstract: Image color data for a field of view is received. Thereafter, color segmentation can be performed on the image color data to define at least one bounding polygon that minimizes an amount of free space within each bounding polygon. The at least one bounding polygon is then used to crop the image color data to result in cropped image color data. Image processing can then be applied to the cropped image color data to identify at least one object therein. Related apparatus, systems, techniques and articles are also described.

Abstract: Systems and methods for managed device-to-device communication in business computing systems are disclosed. An event stream processor is extended with a communication adapter to handle messages from devices using disparate communication protocols (e.g., versions of MQTT). The messages from the devices can be received through a gateway that converts the disparate communication protocols into a common communication protocol (e.g., WebSocket). Specific communication protocols associated with each device, as well as publisher-subscriber relationships among the devices, are established and maintained in communication adapter of the ESP.

Abstract: The present disclosure involves systems and computer implemented methods for creating and managing standalone and distributed models and simulations of Internet of Things (IoT) scenarios. In one example, the method can include presenting a visualization of a model representing an Internet of Things (IoT) scenario on a touch-capable display, the IoT scenario comprising a model of a location and two or more components, the touch-capable display capable of receiving touch-based input from a user interacting with the presented visualization via the display, identifying a selection of a particular component within the IoT scenario via a touch-based command, the touch-based command corresponding to a touch of the particular component within the presented visualization, receiving input defining a modified behavior of the particular component within the IoT scenario, and executing the IoT scenario based on the modified behavior of the particular component.

Abstract: Systems and methods for managed device-to-device communication in business computing systems are disclosed. An event stream processor is extended with a communication adapter to handle messages from devices using disparate communication protocols (e.g., versions of MQTT). The messages from the devices can be received through a gateway that converts the disparate communication protocols into a common communication protocol (e.g., WebSocket). Specific communication protocols associated with each device, as well as publisher-subscriber relationships among the devices, are established and maintained in communication adapter of the ESP.