An image registration method includes: acquiring a target image comprising a target object; inputting the target image to a preset network model, and outputting position information and rotation angle information of the target object; obtaining a reference image comprising the target object by querying a preset image database according to the position information and the rotation angle information; and performing image registration on the target image and the reference image to obtain a corresponding position of the target object of the target image in the reference image.

In the field of video processing, a detection and tracking method and apparatus, and a storage medium, are provided. The method includes: performing feature point analysis on a video frame sequence, to obtain feature points on each video frame thereof; performing target detection on an extracted frame through a first thread based on the feature points, to obtain a target box in the extracted frame; performing target box tracking in a current frame through a second thread based on the feature points and the target box in the extracted frame, to obtain a result target box in the current frame; and outputting the result target box. As the target detection and the target tracking are divided into two threads, a tracking frame rate is unaffected by a detection algorithm, and the target box of the video frame can be outputted in real time, improving real-time performance and stability.

In the field of video processing, a detection and tracking method and apparatus, and a storage medium, are provided. The method includes: performing feature point analysis on a video frame sequence, to obtain feature points on each video frame thereof; performing target detection on an extracted frame through a first thread based on the feature points, to obtain a target box in the extracted frame; performing target box tracking in a current frame through a second thread based on the feature points and the target box in the extracted frame, to obtain a result target box in the current frame; and outputting the result target box. As the target detection and the target tracking are divided into two threads, a tracking frame rate is unaffected by a detection algorithm, and the target box of the video frame can be outputted in real time, improving real-time performance and stability.

The present disclosure provides a method of processing an image, a device, and a medium. The method of processing the image includes: performing an image processing on an original image to obtain a component image for brightness of the original image; determining at least one of the original image and the component image as an image to be processed; classifying a pixel in the image to be processed, so as to obtain a classification result; processing the image to be processed according to the classification result, so as to obtain a target image; and determining an image quality of the original image according to the target image.

Systems and method are claimed for forming an artifact attenuated seismic image. The method includes obtaining an input seismic image, selecting a seismic partition from the input seismic image and determining a seismic dip for the seismic partition. The method further includes determining flattened seismic partition from the seismic partition based, at least in part, on the seismic dip, determining a filtered seismic partition from the flattened seismic partition, and determining an unflattened seismic segment based on the filtered seismic partition. The method still further includes determining the artifact attenuated seismic image based on the unflattened seismic segment. The system includes a seismic source, a plurality of seismic receivers for detecting and recording an observed seismic dataset generated by the radiated seismic wave; and a seismic processor configured form the artifact attenuated seismic image.

A system, method, and computer-readable medium for associating a person’s gestures with specific features of objects is disclosed. Using one or more image capture devices, a person’s gestures and the location of that person in an environment is determined. Using determined distances between the person and objects in the environment and scales associated with features of those objects, the list of specific features in the person’s field-of-view may be determined. Further, a facial expression of the person may be scored and that score associated with one or more specific features.

The present disclosure relates to a method and an apparatus for measuring motility of ciliated cells in a respiratory tract. The method includes the operations of: acquiring image data including a plurality of frames of respiratory tract organoids; identifying positions of ciliated cells by performing motion-contrast imaging on the image data; when a region of interest (ROI) related to the position of the ciliated cells is selected, measuring a ciliary beat frequency (CBF) related to motility of cilia included in the selected region of interest using cross-correlation between the plurality of frames; and expressing the cilia included in the region of interest in a preset display method on the basis of the range of the measured ciliary beat frequency.

The present disclosure relates to a method and an apparatus for measuring motility of ciliated cells in a respiratory tract. The method includes the operations of: acquiring image data including a plurality of frames of respiratory tract organoids; identifying positions of ciliated cells by performing motion-contrast imaging on the image data; when a region of interest (ROI) related to the position of the ciliated cells is selected, measuring a ciliary beat frequency (CBF) related to motility of cilia included in the selected region of interest using cross-correlation between the plurality of frames; and expressing the cilia included in the region of interest in a preset display method on the basis of the range of the measured ciliary beat frequency.

A computing system including a processing circuit in communication with a robot and a camera having a field of view. The processing circuit obtains image information based on the objects in the field of view and a loading environment, the loading environment which includes loading areas, an object queue, and a buffer zone. The computing system is configured to use the obtained image information in motion planning operations for the retrieval and placement of objects from the object queue into the loading environment. Pallets provided within the loading environment (i.e., within the loading areas) are dedicated to receiving objects having corresponding object type identifiers. The computer system further uses the image information to determine the fill status of pallets existing within the loading environment, and whether new pallets need to be brought into the loading environment and/or swapped out with existing pallets to account for future planning and placement operations.

Methods and systems for aligning images of a specimen generated with different modes of an imaging subsystem are provided. One method includes separately aligning first and second images generated with first and second modes, respectively, to a design for the specimen. For a location of interest in the first image, the method includes generating a first difference image for the location of interest and the first mode and generating a second difference image for the location of interest and the second mode. The method also includes aligning the first and second difference images to each other and determining information for the location of interest from results of the aligning.