Abstract: A method of detecting gaps on a support structure includes: obtaining, at an imaging controller, (i) a plurality of depth measurements representing the support structure according to a common frame of reference, and (ii) a plurality of label indicators each defining a label position in the common frame of reference; for each of the label indicators: classifying the label indicator as either a peg label or a shelf label, based on a portion of the depth measurements selected according to the label position and a portion of the depth measurements adjacent to the label position; generating an item search space in the common frame of reference according to the class of the label indicator; and determining, based on a subset of the depth measurements within the item search space, whether the item search space contains an item.

Abstract: According to one embodiment, a method, computer system, and computer program product for concealing distracting user interface elements within collaborative editing software is provided. The present invention may include monitoring activity on a computing device to identify the presence of collaborative editing and presentation programs, and responsive to determining that presenting users are conducting a presentation and that users are editing a digital collaborative document, concealing one or more graphical user interface elements; and, responsive to determining that the one or more presenting users are no longer conducting the presentation, graphically summarizing one or more changes to the digital collaborative document made during the presentation.

Abstract: Provided are a computer program product, system, and method for using classifications from text to determine instances of graphical element types to include in a template layout for digital media output. Text is processed to determine classifications. The determined classifications of the text are inputted to a machine learning module to output instances for graphical element types. The outputted instances of the graphical element types are rendered in a user interface for a user to select. User selection is received of one of the instances rendered in the user interface for each of the graphical element types. The text with the user selected instances for the graphical element types are rendered in a template layout. The template layout including the text rendered with the user selected instances for the graphical element types is rendered in an output layout of digital media.

Abstract: A method by an imaging controller of detecting item facings from image sensor data includes: obtaining, at the imaging controller, the image sensor data corresponding to a support structure containing at least one item; identifying, by a feature detector of the imaging controller, a set of matched keypoint pairs from keypoints of the image sensor data; determining, by a peak detector of the imaging controller, a separation distance between the keypoints of each matched keypoint pair; detecting, by the peak detector, a count of item instances represented in the image sensor data based on the separation distances; and presenting item facing detection output including the count of item instances.

Abstract: According to one embodiment, a method, computer system, and computer program product for concealing distracting user interface elements within collaborative editing software is provided. The present invention may include monitoring activity on a computing device to identify the presence of collaborative editing and presentation programs, and responsive to determining that presenting users are conducting a presentation and that users are editing a digital collaborative document, concealing one or more graphical user interface elements; and, responsive to determining that the one or more presenting users are no longer conducting the presentation, graphically summarizing one or more changes to the digital collaborative document made during the presentation.

Abstract: A method, computer program product, and system includes a processor(s) continuously monitoring a current condition of a user of an Internet of Things (IoT) device, via the IoT device. The processor(s) determines that the current condition indicates an issue with the well-being of the user. The processor(s) identifies upcoming event(s), within a given temporal period, in which the user will participate. The processor(s) determines that the current condition of the user will negatively impact at least one event of the upcoming event(s). The processor(s) generates action(s) comprising a change to the event, where the action(s) is executed by interacting with one or more applications deployed on the one or more target computer resources (accessible to the one or more processors via a network connection). The processor(s) automatically executes the at least one action on the one or more target computer resources.

Abstract: A method, computer program product, and system includes a processor(s) continuously monitoring a current condition of a user of an Internet of Things (IoT) device, via the IoT device. The processor(s) determines that the current condition indicates an issue with the well-being of the user. The processor(s) identifies upcoming event(s), within a given temporal period, in which the user will participate. The processor(s) determines that the current condition of the user will negatively impact at least one event of the upcoming event(s). The processor(s) generates action(s) comprising a change to the event, where the action(s) is executed by interacting with one or more applications deployed on the one or more target computer resources (accessible to the one or more processors via a network connection). The processor(s) automatically executes the at least one action on the one or more target computer resources.

Abstract: Aspects of this disclosure relate to humanizing a chatbot. A message that includes a prompt is received from a user. Data of the user is gathered. Using the data, a language imperfection associated with the user is identified. A reply to the prompt that includes the language imperfection is generated.

Abstract: A method in an imaging controller of detecting obstructions on a front of a support structure includes: obtaining (i) a point cloud of the support structure and an obstruction, and (ii) a support structure plane corresponding to the front of the support structure; for each of a plurality of selection depths: selecting a subset of points from the point cloud based on the selection depth; detecting obstruction candidates from the subset of points and, for each obstruction candidate: responsive to a dimensional criterion being met, determining whether the obstruction candidate meets a confirmation criterion; when the obstruction candidate meets the confirmation criterion, identifying the obstruction candidate as a confirmed obstruction; and presenting obstruction detection output data including the confirmed obstructions.

Abstract: A method of detecting product facings from captured depth and image data includes: obtaining, at an imaging controller, (i) depth measurements representing a support structure supporting a plurality of product facings, (ii) image data representing the support structure, and (iii) a set of region of interest (ROI) indicators each indicating a position of a plurality of the product facings; generating a first set of candidate facing edges from the depth measurements; generating a second set of candidate facing edges from the image data; generating a third set of candidate facing edges by combining the first and second sets; generating, for each adjacent pair of the third set of candidate facing edges, a candidate facing boundary; selecting a subset of output facing boundaries from the candidate facing boundaries, based on the ROI indicators; and storing the output facing boundaries in a memory coupled to the imaging controller.

Abstract: A method of detecting gaps on a support structure includes: obtaining, at an imaging controller, (i) a plurality of depth measurements representing the support structure according to a common frame of reference, and (ii) a plurality of label indicators each defining a label position in the common frame of reference; for each of the label indicators: classifying the label indicator as either a peg label or a shelf label, based on a portion of the depth measurements selected according to the label position and a portion of the depth measurements adjacent to the label position; generating an item search space in the common frame of reference according to the class of the label indicator; and determining, based on a subset of the depth measurements within the item search space, whether the item search space contains an item.

Abstract: A method of recovering label positions in an imaging controller includes: receiving (i) a definition of a plane containing edges of the shelf, and (ii) a plurality of initial label indicators having locations on the plane; assigning the initial label indicators among a plurality of candidate subsets each representing a single physical label; for each candidate subset of initial indicators: generating, for each of a plurality of projection depths relative to the plane, a set of projections of the initial indicators in the candidate subset; determining an aggregate surface area for each set of projections; selecting, as a recovered depth for the candidate subset, one of the projection depths corresponding to the minimum aggregate surface area; and generating a recovered position for the candidate subset based on the recovered depth; and storing the recovered positions.

Abstract: A computer identifies entity-containing content. The computer analyzes the entity-containing content for entities. The computer identifies a plurality of hierarchy levels for the entities. The computer receives selections of highlights for the entities, wherein the highlights for the entities within each hierarchy level share one or more characteristics. The computer applies entity contrasting. The computer outputs the entity-containing content with applied entity contrasting to a user.

Abstract: A method of object detection includes obtaining a set of images depicting overlapping regions of an area containing a plurality of objects. Each image includes input object indicators defined by input bounding boxes, input confidence level values, and object identifiers. The method includes identifying candidate subsets of input object indicators in adjacent images. Each candidate subset has input overlapping bounding boxes in a common frame of reference, and a common object identifier. The method includes adjusting the input confidence levels for each input object indicator in the candidate subsets; selecting clusters of the input object indicators satisfying a minimum input confidence threshold, having a common object identifier, and having a degree of overlap satisfying a predefined threshold; and detecting an object by generating a single output object indicator for each cluster, the output object indicator having an output bounding box, an output confidence level value, and the common object identifier.

Abstract: Processors are configured to analyze message text content to determine whether the text content proposes a meeting event at a specified location and a specified time. In response to determining that the text content proposes said meeting event, processors determine whether a meeting is possible at the specified location and the specified time as a function of forum availability. In response to determining that the meeting is possible, some processors generate a confirming appointment message comprising text content that identifies creation of a meeting event at the meeting place at the specified location and at the specified time. In response to determining that the meeting is not possible, processors create an alternative meeting proposal message that includes alternative text content, including an alternative, different location or an alternative, different time.

Abstract: A method of auxiliary label detection includes: at an imaging controller, obtaining (i) an image of a support structure and (ii) a plurality of primary label indicators each defining a position of a primary label within the image; at the imaging controller, selecting a detection region from the image based on a reference indicator; at the imaging controller, detecting an auxiliary label within the detection region based on predefined visual attributes of the auxiliary label; at the imaging controller, selecting one of the primary label indicators based on proximity between the auxiliary label and the selected primary label indicator; updating the selected primary label indicator with an identifier of the auxiliary label; and storing the updated primary label indicator in a memory.

Abstract: An embodiment of the invention may include a method, computer program product and system for communicating information to a user via a graphical user interface of a computer. An embodiment may include displaying a visual cue corresponding to a suggestion for text substitution within a text representation of a media file, wherein the suggestion for text substitution is generated in response to identification of any one or combination of a repeated word, a repeated phrase, and a filler, and wherein the suggestion for text substitution is based on an aggregation of one or more of characteristics of the text representation of the media file.

Abstract: Provided are techniques generating graphs based on reading and listening patterns. Key concepts of a content item are identified using text analysis. Focus elements that are focused on by a consumer of the content item are identified. The key concepts are compared with the focus elements to identify overlapping elements. A graph that includes components is generated with the overlapping elements, wherein the graph reflects understanding of the content item from a perspective of the consumer. The components are modified based on component identifiers. The graph is provided to one or more users.

Abstract: A method of determining a support structure depth of a support structure having a front and a back separated by the support structure depth includes: obtaining a point cloud of the support structure, and a mask indicating, for a plurality of portions of an image of the support structure captured from a capture pose, respective confidence levels that the portions depict the back of the support structure; selecting, from the point cloud, an initial set of points located within a field of view originating at the capture pose; selecting, from the initial set of points, an unoccluded subset of depth measurements, the depth measurements in the unoccluded subset corresponding to respective image coordinates; retrieving, from the mask, a confidence level for each of the depth measurements in the unoccluded subset; and based on the depth measurements in the unoccluded subset and the retrieved confidence levels, determining the support structure depth.

Abstract: A method of object detection includes obtaining a set of images depicting overlapping regions of an area containing a plurality of objects. Each image includes input object indicators defined by input bounding boxes, input confidence level values, and object identifiers. The method includes identifying candidate subsets of input object indicators in adjacent images. Each candidate subset has input overlapping bounding boxes in a common frame of reference, and a common object identifier. The method includes adjusting the input confidence levels for each input object indicator in the candidate subsets; selecting clusters of the input object indicators satisfying a minimum input confidence threshold, having a common object identifier, and having a degree of overlap satisfying a predefined threshold; and detecting an object by generating a single output object indicator for each cluster, the output object indicator having an output bounding box, an output confidence level value, and the common object identifier.