Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support creation and execution of automated sequences of user interface (UI) interactions. To facilitate creation and execution of automated sequences of UI interactions, an automation engine is provided and includes a model configured to capture image data when creating the sequence of UI interactions. The model may also be used during replay of the sequence of UI interactions. For example, the model may be used during replay of the sequence of UI interactions to locate UI elements corresponding to the UI interactions, or to perform pre-and/or post-validation of action execution. The automation engine may also provide processes to enable location of dynamic content, such as UI elements that may be presented in different or unexpected locations, and processes to address complex UI elements, such as data grids, tree views, and drawings (e.g., CAD drawings).

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support creation and execution of automated sequences of user interface (UI) interactions. To facilitate creation and execution of automated sequences of UI interactions, an automation engine is provided and includes a model configured to capture image data when creating the sequence of UI interactions. The model may also be used during replay of the sequence of UI interactions. For example, the model may be used during replay of the sequence of UI interactions to locate UI elements corresponding to the UI interactions, or to perform pre-and/or post-validation of action execution. The automation engine may also provide processes to enable location of dynamic content, such as UI elements that may be presented in different or unexpected locations, and processes to address complex UI elements, such as data grids, tree views, and drawings (e.g., CAD drawings).

An autonomous farming machine navigable in an environment for performing farming action(s) is disclosed. The farming machine receives a notification from a manager that there are no obstacles in the blind spots of the detection system. The farming machine applies an obstacle detection model to the captured images to verify that there are no obstacles in unobstructed views. The farming machine determines a configuration of the farming machine. The farming machine determines a virtual safety bubble for the farming machine to autonomously perform the farming action(s) based on the determined configuration. The farming machine detects an obstacle in the environment by applying the obstacle detection model to the captured images. The farming machine determines that the obstacle is entering the virtual safety bubble. In response to determining that the obstacle is entering the virtual safety bubble, the farming machine terminates operation of the farming machine and/or enacts preventive measures.

An autonomous farming machine navigable in an environment for performing farming action(s) is disclosed. The farming machine receives a notification from a manager that there are no obstacles in the blind spots of the detection system. The farming machine applies an obstacle detection model to the captured images to verify that there are no obstacles in unobstructed views. The farming machine determines a configuration of the farming machine. The farming machine determines a virtual safety bubble for the farming machine to autonomously perform the farming action(s) based on the determined configuration. The farming machine detects an obstacle in the environment by applying the obstacle detection model to the captured images. The farming machine determines that the obstacle is entering the virtual safety bubble. In response to determining that the obstacle is entering the virtual safety bubble, the farming machine terminates operation of the farming machine and/or enacts preventive measures.

Methods for submitting an insurance claim for damaged motor vehicle glass are provided that can include: receiving a plurality of images associated with motor vehicle glass at processing circuitry; performing image processing operations on each of the plurality of images to determine one or more of glass damage, glass type, and/or claim fraud; and submitting an insurance claim for motor vehicle glass repair or replace based on the glass type or damage, or flagging the claim as fraud.

The present disclosure also provides a non-transitory computer readable storing instruction that when executed by a processor, causes a computer system to perform the following method. The method can include: prompting a user for initial claim submission information; prompting the user for a plurality of images of portions of motor vehicle glass; performing image processing operations on each of the plurality of images to train or improve the computer system, determine one or more of glass damage, glass type, and/or claim fraud; and one of submit or reject an insurance claim for glass repair.

Glass vendors may be granted access to the systems and methods of the present disclosure and prompted to complete replacements as well.

Methods for submitting an insurance claim for damaged motor vehicle glass are provided that can include: receiving a plurality of images associated with motor vehicle glass at processing circuitry; performing image processing operations on each of the plurality of images to determine one or more of glass damage, glass type, and/or claim fraud; and submitting an insurance claim for motor vehicle glass repair or replace based on the glass type or damage, or flagging the claim as fraud.

The present disclosure also provides a non-transitory computer readable storing instruction that when executed by a processor, causes a computer system to perform the following method. The method can include: prompting a user for initial claim submission information; prompting the user for a plurality of images of portions of motor vehicle glass; performing image processing operations on each of the plurality of images to train or improve the computer system, determine one or more of glass damage, glass type, and/or claim fraud; and one of submit or reject an insurance claim for glass repair.

Glass vendors may be granted access to the systems and methods of the present disclosure and prompted to complete replacements as well.

A visualization device of a 3D augmented object for displaying a pickup target in a manufacturing process assembly operation includes: a component information DB in which attribute information of at least one or more components is stored; a component information input that receives component information from a wearable device; a path generator that generates path information from the real-time location to the component location included in the component information by calling the data corresponding to the component information entered to the component information input from the component information DB and detecting the real-time location of the wearable device; and a direction guide that outputs a directional image and an expected distance to the component location to the wearable device, based on the path information generated by the path generator.

A visualization device of a 3D augmented object for displaying a pickup target in a manufacturing process assembly operation includes: a component information DB in which attribute information of at least one or more components is stored; a component information input that receives component information from a wearable device; a path generator that generates path information from the real-time location to the component location included in the component information by calling the data corresponding to the component information entered to the component information input from the component information DB and detecting the real-time location of the wearable device; and a direction guide that outputs a directional image and an expected distance to the component location to the wearable device, based on the path information generated by the path generator.

Color and exposure matching for systems, such as a videoconferencing endpoint, that have overlapping camera fields of view. The geometric relationships between the overlapping cameras are used to determine correction processing. For each camera, histograms are developed for the overlapping cameras. A dynamic threshold is determined for each histogram. Using the dynamic threshold, peak detection is performed on each histogram. Using the geometric relationships, expected histogram relationships are determined. The actual histogram relationships are compared to the expected relationships, with further processing based on the correctness of the comparison. In some of the cases of further processing, peaks of the histograms are compared to find matching and non-matching peaks. Various ratios of pixels in the various peaks are used to determine needed changes to respective cameras. Incremental changes to camera outputs are provided and accumulated so that overall changes can be provided to adjust the output of the respective cameras.

Color and exposure matching for systems, such as a videoconferencing endpoint, that have overlapping camera fields of view. The geometric relationships between the overlapping cameras are used to determine correction processing. For each camera, histograms are developed for the overlapping cameras. A dynamic threshold is determined for each histogram. Using the dynamic threshold, peak detection is performed on each histogram. Using the geometric relationships, expected histogram relationships are determined. The actual histogram relationships are compared to the expected relationships, with further processing based on the correctness of the comparison. In some of the cases of further processing, peaks of the histograms are compared to find matching and non-matching peaks. Various ratios of pixels in the various peaks are used to determine needed changes to respective cameras. Incremental changes to camera outputs are provided and accumulated so that overall changes can be provided to adjust the output of the respective cameras.