Systems, devices, methods, and computer processing products for automatically checking for errors in segmentation (contouring) using heuristic and/or statistical evaluation methods.

In variants, the method can include: detecting a property within a set of measurements; determining a set of property parameters based on the detection; determining a set of higher-resolution measurements based on the set of property parameters; and determining a set of property attributes based on the set of higher-resolution measurements.

Implementations are described herein for analyzing a sequence of digital images captured by a mobile vision sensor (e.g., integral with a robot), in conjunction with information (e.g., ground truth) known about movement of the vision sensor, to determine spatial dimensions of object(s) and/or an area captured in a field of view of the mobile vision sensor. Techniques avoid the use of visual indicia of known dimensions and/or other conventional tools for determining spatial dimensions, such as checkerboards. Instead, techniques described herein allow spatial dimensions to be determined using less resources, and are more scalable than conventional techniques.

A computer-implemented method allows a wait time to be determined automatically for a queue area. The queue is part of an environment and includes defined entrance and exit areas. A series of images showing the environment are received over time. A wait time associated with the queue area is determined by detecting a location of a object corresponding to a person in a first one of the images; associating the object with an identifier uniquely identifying the object in the first one of the images matching objects in later images; and determining the wait time based on times associated with an image in which an object associated with the identifier enters the queue area through the defined entrance area and later one of the images in which an object associated with the identifier exits the queue area through the defined exit area. An indication of the wait time is output.

A moving object detection system detecting moving objects based on a captured image comprising: cameras capturing images to generate image data; image recognition circuitries each performing image recognition on the image data generated by each camera to detect a moving object in a captured image indicated by the image data; and an information management apparatus managing image data supplied from each camera to a corresponding image recognition circuitry. The information management apparatus includes a communication interface performing data communication with the cameras and the image recognition circuitries, and a controller managing congestion information on the number of moving objects localized within a range of a captured image indicated by image data for each camera, and controlling the communication interface to supply the image data generated by the cameras to each image recognition circuitry, distributing the image data according to the congestion information.

Provided is image processing unit that causes computer to perform: a spatter candidate region detection step of performing, for each of input images obtained by capturing workpiece during arc welding, detection of a spatter candidate region based on a pixel value indicating brightness of a pixel included in the input images; a reflected light region identification step of identifying, in the spatter candidate region detected in the spatter candidate region detection step, a reflected light region in which reflected light of arc light is shown, based on color information of a reference pixel included in the spatter candidate region; and a spatter number identification step of identifying, as the number of spatters, the number of spatter candidate regions obtained by removing the reflected light region identified in the reflected light region identification step in the spatter candidate region detected in the spatter candidate region detection step.

A mixed reality (MR) providing device is disclosed. The MR providing device includes: a camera, a communication unit comprising circuitry configured to communicate with an electronic device providing video, an optical display unit comprising a display configured to simultaneously display real space within a preset range of viewing angle and a virtual image, and a processor. The processor is configured to: capture the preset range of viewing angle through the camera to acquire an image, identify at least one semantic anchor spot of the acquired image in which an object may be positioned, transmit characteristic information of the semantic anchor spot related to the object that may be positioned to the electronic device through the communication unit, receive an object region including the object corresponding to the characteristic information and included in an image frame of the video from the electronic device through the communication unit, and control the optical display unit to display the received object region on the semantic anchor spot.

In one aspect, there is provided a method that includes receiving, by a control system having (i) a first camera configured to obtain an image of a scene, (ii) a winch controller, and (iii) a feeding system configured to deliver a feed to aquaculture, instructions to initiate a calibration of the first camera, determining a calibration state of the first camera, determining a sequence of calibration steps based on the calibration state of the first camera, and executing the sequence of calibration steps to calibrate the first camera.

A crop detection system and method of using the same includes a machine vision system mounted to a mobile vehicle. The machine vision system includes an information capturing device connected to a computer having a processor and memory. The memory includes stored crop and field information. Positioning members are mounted to an extend forward of the mobile structure. The information capturing device includes a camera, a sensor, a transceiver and/or a stereo sensor configuration and is positioned to sense the presence, size, location and orientation of characteristics of a crop.

Embodiments of this invention provide a measurement map configuration method and apparatus. A wafer to be inspected is provided. The wafer includes a plurality of inspection marks. A first inspection result is obtained based on a first set of inspection marks. A second set of inspection marks is selected based on a preset rule. The second set of inspection marks is less than the first set of inspection marks. A second inspection result is obtained based on the second set of inspection marks. If an overlay accuracy of the second inspection result matches an overlay accuracy the first inspection result, a measurement map for the wafer is set based on target inspection marks. The target inspection marks are the second set of inspection marks of the measurement map.