Abstract: A computing system including a processing circuit in communication with a camera having a field of view. The processing circuit is configured to perform operations related to detecting, identifying, and retrieving objects disposed amongst a plurality of objects. The processing circuit may be configured to perform operations related to object recognition template generation, feature generation, hypothesis generation, hypothesis refinement, and hypothesis validation.

Abstract: An image forming apparatus includes a reception unit and a controller. The reception unit is configured to receive a plurality of image data in a sequential manner. The controller is configured to perform control, in a case where first image data among the plurality of image data is received, so as not to start printing upon reception of the first image data in a case where the first image data has a different print setting from second image data received before the first image data, and perform control, in a case where third image data received after the first image data has a same print setting as the second image data, so as to arrange, in a main scan direction of a sheet, image data having the same print setting and including not the first image data but the second image data and the third image data to start printing.

Abstract: Automated techniques are for generating a large volume of diverse training data that can be used for training machine learning models to extract KV pairs from document images. Given a single input document image and associated annotation data, a large number of diverse synthetic training datapoints are automatically generated by a synthetic data generation system, each datapoint including a synthetic document image and associated annotation data. The generated synthetic training datapoints can be used to train and improve the performance of ML models for extracting KV pairs from document images. In certain implementations, multiple synthetic datapoints are generated by varying the values associated with a key for a content item within the input document image.

Abstract: The disclosed system provides automatic composition of a presentation video of shared content with a rendering of a selected presenter. When a speaker is giving a presentation and providing shared content projected on a screen to in-room attendees, a system provides the composite presentation video with on-line attendees. The system can select one in-room attendee as the presenter based on one or more factors. For instance, the system may select a person that is positioned closer to an object, such as a podium. A person may also be selected based on other types of interaction with an object, e.g., whether a person is touching a podium. Automatic selection of a user and automatic generation of the composite presentation video allows a system to share the in-room dynamics with remote participants of a hybrid meeting.

Abstract: A processing apparatus includes: a storage that stores a plurality of instructions; and a processor that executes the plurality of instructions. The plurality of instructions, when executed by the processor, cause the processor to perform: providing a setting screen for setting one or more items relating to the processing apparatus; and setting the one or more items in response to operation performed on the setting screen. The setting screen includes a first setting screen for receiving operation performed by a person, and a second setting screen for receiving operation automated by Robotic Process Automation.

Abstract: An image processing system includes a microscope system that acquires an input image to be input to an image processing device, and the image processing device including a circuitry. The circuitry selects a learned model from a plurality of learned models that have learned image conversion that converts the input image into an output image having an image quality higher than an image quality of the input image, and performs the image conversion using the selected learned model. Each of the plurality of learned models is a learned model learned using an image that differs from an image(s) used by the other learned model(s) in at least sample type, or a learned model learned using an image that differs from an image(s) used by the other learned model(s) in at least image quality range.

Abstract: Disclosed are a print region editing device and a method thereof. When an image is released during enlargement, reduction, or movement within a preset guideline portion, a print region rectangle or print region square of a longer-side length and a shorter-side length is configured according to a long-short ratio of the guide line portion and a long-short ratio of the corresponding image, and the corresponding image is enlarged or maintained so that four vertices of the corresponding image match four vertices of the configured print region rectangle or print region square, thereby freely changing a paper-full format and an image-full format depending on the enlargement or reduction of the image.

Abstract: The present invention provides an image shooting method and an electronic device. The image shooting method includes: receiving a first input; in response to the first input, obtaining a first video stream and a second video stream with a same shot content acquired by a camera module; extracting a target object in the shot content of the first video stream to obtain a first intermediate video stream of the target object; removing the target object in the shot content of the second video stream and performing image registration compensation on areas at which the target object is located, to obtain a second intermediate video stream; and generating, based on the first intermediate video stream and the second intermediate video stream, a target video; where the first intermediate video stream and the second intermediate video stream are different in frame rate.

Abstract: An image processing apparatus includes an interface and a processor. The interface acquires printing data including an image. If length in a longitudinal direction of the image is larger than a printing width of a medium on which the image is printed, the processor rotates the image.

Abstract: A method for enhancing image quality may be provided. The method may include receiving a plurality of input frames and metadata, and determining one or more feature scores for a received input frame from the plurality of input frames. The method may further include determining a parametric score for the received input frame based on an analysis of the one or more feature scores of the received input frame and the metadata. The method may include identifying one or more artifacts for correction in the received input frame based on the parametric score, and determining a strength of correction required for at least one identified artifact in the received input frame based on the parametric score, then applying the determined strength of correction to the received input frame. The method may further include performing multi-frame blending for a plurality of received input frames with applied determined strength of correction.

Abstract: A system and method for a 3D printer with one time use files that incorporates a software and a 3D printer to perform the method. In a first phase the software is used to configure a machine ID number, a file ID number and create an OBJ file and a number of prints for the OBJ file in a modified OBJ file. In a second phase the modified OBJ file is encrypted to a G file. In a third phase the G file is introduced to the 3D printer. The 3D printer validates the machine ID number and the file ID number of the G file. In a fourth phase the 3D printer prints a design contained in the G file the predetermined number of times that G file indicates. The 3D printer stores the file ID number to prevent the G file being printed again.

Abstract: An information processing apparatus includes an input interface, a processor, and an output interface. The input interface obtains observation data obtained from an observation space. The processor detects a detection target included in the observation data. The processor maps coordinates of the detected detection target as coordinates of a detection target in a virtual space, tracks a position and a velocity of a material point indicating the detection target in the virtual space, and maps coordinates of the tracked material point in the virtual space as coordinates in a display space. The processor sequentially observes a size of the detection target in the display space and estimates a size of a detection target at a present time on a basis of observed values of a size of a detection target at the present time and estimated values of a size of a past detection target.

Abstract: An image processing system includes: a first processor that is mounted on an image processing apparatus including at least one of an image forming unit that performs processing of forming an image on a medium or an image scanning unit that performs processing of scanning an image on a medium; and a second processor that is mounted on a control apparatus that is connected to the image processing apparatus via a virtual leased line, and controls a part of at least one of the processing of forming an image on a medium or the processing of scanning an image on a medium performed by the image processing apparatus, in which the first processor is configured to: in a case where an event to be recorded in a log occurs in the image processing apparatus, transmit log information regarding the event to the control apparatus via the virtual leased line being connected or after connecting the virtual leased line in a case where the virtual leased line is not connected; and the second processor is configured to: in a case

Abstract: A method for authenticating a food package holding a food product can include receiving sample image data depicting the food package, identifying a sample print feature sub-set of the food package, identifying a sample geometric feature sub-set of the food package, generating a sample feature set based on the sample print feature sub-set and the sample geometric feature sub-set, receiving a reference feature set, wherein the reference feature set is generated based on a reference print feature sub-set and a reference geometric feature sub-set identified in reference image data, wherein the reference image data is captured in a food packaging system arranged to produce food packages, comparing the sample feature set and the reference feature set, and in case of match, providing an indication that the food package is authentic.

Abstract: A method for three-dimensional edge detection includes obtaining, for each of plural two-dimensional slices of a three-dimensional image, a two-dimensional object detection result and a two-dimensional edge detection result, stacking the two-dimensional object detection results into a three-dimensional object detection result, and stacking the two-dimensional edge detection results into a three-dimensional edge detection result. The method also includes performing encoding according to a feature map of the three-dimensional image, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an encoding result, and performing decoding according to the encoding result, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an optimized three-dimensional edge detection result of the three-dimensional image.

Abstract: An information processing apparatus, an information processing system, and an information processing method. The information processing apparatus transmits input screen information for displaying an input screen for receiving input of a workflow including a plurality of components to a communication terminal communicably connected to the information processing apparatus, sets the workflow including a component whose usage history is to be counted according to an operation on the input screen displayed at the communication terminal based on the input screen information, and in response to an execution of the workflow, counts the usage history of the component to be counted included in the workflow.

Abstract: Examples disclosed herein involve a computing system configured to (i) based on image data captured by a vehicle in an environment, obtain observations of a time-sequence of positions of an agent identified within the image data, (ii) generate a first updated time-sequence of positions of the agent by performing a first optimization operation that includes processing the observed time-sequence of positions by beginning with a position associated with an observation having the highest confidence in the time-sequence of observations and proceeding in a first direction, (iii) after generating the first updated time-sequence of positions, generate a second updated time-sequence of positions of the agent by performing a second optimization operation that includes processing the first updated time-sequence of positions in a second direction opposite the first direction, and (iv) derive a trajectory for the agent in the environment based on the second updated time-sequence of positions for the agent.

Abstract: An acquisition portion of a pretreatment control apparatus acquires identification information capable of identifying a treatment medium (step S1). A first transmission portion transmits a pretreatment instruction based on the identification information to a pretreatment device which performs a pretreatment with respect to the treatment medium (step S13). A second transmission portion transmits a transmission instruction for identified print data based on the identification information, to a storage device which stores print data (step S3). As a result, the pretreatment control apparatus can transmit the pretreatment instruction and the identified print data by acquiring a single piece of identification information. Therefore, the number of processing steps by the pretreatment control apparatus is fewer than when the pretreatment instruction and the identified print data are transmitted by acquiring different information.

Abstract: An inspection apparatus (10) includes: a three-dimensional sensor (11) configured to irradiate a member to be inspected with a beam and acquire point cloud data of the member to be inspected based on at least amplitude information of light; a direction identifying unit (12) configured to identify a predetermined direction in which there are the largest number of the point cloud data in the reference coordinate system which is coordinate axes for the member to be inspected; and a tilt amount determination unit (13) configured to determine a tilt amount for changing an arrangement of the reference coordinate system so that the number of the point cloud data in the predetermined direction increases in the eigen coordinate system which is coordinate axes for the three-dimensional sensor (11).

Abstract: A technique for performing convolution operations is disclosed. The technique includes performing a first convolution operation based on a first convolutional layer input image to generate at least a portion of a first convolutional layer output image; while performing the first convolution operation, performing a second convolution operation based on a second convolutional layer input image to generate at least a portion of a second convolutional layer output image, wherein the second convolutional layer input image is based on the first convolutional layer output image; storing the portion of the first convolutional layer output image in a first memory dedicated to storing image data for convolution operations; and storing the portion of the second convolutional layer output image in a second memory dedicated to storing image data for convolution operations.