One example system for displaying immersive scenes includes a processor and at least one memory device. The memory device includes instructions that are executable by the processor to cause the processor to receive a collection of metadata associated with an immersive scene, identify each of a plurality of properties of the immersive scene based on the collection of metadata, receive a dynamic immersive background, receive a plurality of video streams associated with a video conference, and display each of the plurality of video streams in the immersive scene based at least in part of the plurality of properties of the immersive scene and on the dynamic immersive background.

A computer-implemented method includes receiving a 3D model representative of upper teeth (U1) of a patient (P) and receiving a plurality of images of a face of the patient (P). The method also includes generating a facial model (200) of the patient based on the received plurality of images and determining, based on the determined facial model (200), the received 3D model of 10 the upper teeth (U1) and the plurality of images, a spatial relationship between the upper teeth (U1) of the patient (P) and a facial skeleton of the patient (P).

The present invention relates to a method for deriving a 3D data from image data comprising: receiving, from at least one camera, image data representing an environment; detecting, from the image data, at least one object within the environment; classifying the at least one detected object, wherein the method comprises, for each classified object of the classified at least one objects: determining a 2D skeleton of the classified object by implementing a neural network to identify features of the classified object in the image data corresponding to the classified object; and constructing a 3D skeleton for the classified object, comprising mapping the determined 2D skeleton to 3D.

Provided are a pedestrian search method, a server, and a storage medium. The pedestrian search method is described as follows: a pedestrian detection is performed on each segment of monitoring video to obtain multiple pedestrian tracks, where each pedestrian track of the multiple pedestrian tracks includes multiple video frame images of a same pedestrian; and pedestrian tracks belonging to the same pedestrian is determined according to video frame images in the multiple pedestrian tracks, and the pedestrian tracks of the same pedestrian are merged.

An information processing device according to the present disclosure includes: an acquisition unit that acquires outline information indicating an outline of a user who makes a body motion; and a specification unit that specifies, among body parts, a main part corresponding to the body motion and a related part, which is to be a target of correction processing of motion information corresponding to the body motion, on the basis of the outline information acquired by the acquisition unit.

Normalized resolutions are determined for first and second regions of interest of an initial video stream captured by a video capture device located within a physical space. The first region of interest is associated with a first conference participant within the physical space and the second region of interest is associated with a second conference participant within the physical space. Instructions are transmitted to the video capture device to cause the video capture device to capture, at the normalized resolutions, a first video stream associated with the first region of interest and a second video stream associated with the second region of interest. The first and second video streams conform sizes and quality levels of the first and second conference participants within separate user interface tiles of a conferencing software user interface to which the first and second video streams are output.

The invention provides for a medical apparatus (100, 300, 400) comprising a subject support (102) configured for moving a subject (106) from a first position (124) to a second position (130) along a linear path (134). The subject support comprises a support surface (108) for receiving the subject. The subject support is further configured for positioning the subject support in at least one intermediate position (128). The subject support is configured for measuring a displacement (132) along the linear path between the first position and the at least one intermediate position. Each of the at least one intermediate position is located between the first position and the second position. The medical apparatus further comprises a camera (110) configured for imaging the support surface in the first position. Execution of machine executable instructions 116 cause the a processor (116) controlling the medical apparatus to: acquire (200) an initial image (142) with the camera when the subject support is in the first position; control (202) the subject support to move the subject support from the first position to the second position; acquire (204) at least one intermediate image (144) with the camera and the displacement for each of the at least one intermediate image as the subject support is moved from the first position to the second position; and calculate (206) a height profile (150, 600, 604) of the subject by comparing the initial image and the at least one intermediate image. The height profile is at least partially calculated using the displacement. The height profile is descriptive of the spatially dependent height of the subject above the support surface.

A device including sensors and a processor. The sensors are configured to detect movements of a user. The processor is configured to categorize the movements of the user as a micro-movement or a macro-movement; quantify a number of the micro-movements; quantify a number of the macro-movements; determine based upon the number of micro-movements whether a body part of interest of a user is supported; and provide feedback to the user if the body part of interested is unsupported and continuing to monitor the body part of interest if the user is supported without providing any feedback.

A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

A surgical item managing method for use in a smart operating room to manage a surgical item used during a surgical procedure is provided. The surgical item includes a flexible RFID tag. The method includes the steps of: obtaining an information about a position of the flexible RFID tag; photographing a patient to obtain a position of the patient; determining if the position of the flexible RFID tag and the position of the patient overlap, to determine if the position of the flexible RFID tag is in the body of the patient; and giving a warning when the position of the flexible RFID tag is in the body of the patient.