Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

An image processing apparatus acquires first shape information representing a three-dimensional shape about an object located within an image capturing region based on one or more images obtained by one or more imaging apparatuses for performing image capturing of the image capturing region from a plurality of directions, acquires second shape information representing a three-dimensional shape about an object located within the image capturing region based on one or more images obtained by one or more imaging apparatuses, acquires viewpoint information indicating a position and direction of a viewpoint, and generates a virtual viewpoint image corresponding to the position and direction of the viewpoint indicated by the acquired viewpoint information based on the acquired first shape information and the acquired second shape information, such that at least a part of the object corresponding to the second shape information is displayed in a translucent way within the virtual viewpoint image.

Disclosed are methods and apparatuses for image data encoding/decoding. A method of decoding an image includes receiving a bitstream in which the image is encoded; obtaining index information for specifying a block division type of a current block in the image; and determining the block division type of the current block from a candidate group pre-defined in the decoding apparatus. The candidate group includes a plurality of candidate division types, including at least one of a non-division, a first quad-division, a second quad-division, a binary-division or a triple-division. The method also includes dividing the current block into a plurality of sub-blocks; and decoding each of the sub-blocks with reference to syntax information obtained from the bitstream.

An augmented reality glasses device including a pair of transmissive display sections and capable of displaying a path of a tool in a machine tool on the display sections includes a block acquisition section that acquires a program block causing the tool to move and operate, a path determination section that determines a path and a movement direction of the tool in a workpiece coordinate system in accordance with a plurality of the acquired successive time-series program blocks, and a display control section that causes the display sections to stereographically display the determined path and movement direction of the tool.

A method of operating a data processing system is disclosed for a data processing system that comprises a display and a display controller operable to provide to the display data in respect of output surfaces to be displayed. The method comprises, when an output surface is to be displayed, the display controller providing to the display data in respect of the output surface in the form of image data and image modification data, and the display using the image data and the image modification data when producing an output surface for display.

Disclosed are methods and apparatuses for image data encoding/decoding. A method of decoding an image includes receiving a bitstream in which the image is encoded; obtaining index information for specifying a block division type of a current block in the image; and determining the block division type of the current block from a candidate group pre-defined in the decoding apparatus. The candidate group includes a plurality of candidate division types, including at least one of a non-division, a first quad-division, a second quad-division, a binary-division or a triple-division. The method also includes dividing the current block into a plurality of sub-blocks; and decoding each of the sub-blocks with reference to syntax information obtained from the bitstream.

A location identification system analyzes information received corresponding to a device detected in a room of a patient. On detecting a location identification of the device, the system assigns the device to the location corresponding to the location identification. In embodiments, the system retrieves patient and care team information for the location. The location and patient and care team information may be communicated to a central video monitoring system.

An apparatus for generating view images for a scene comprises a store (101) which stores three dimensional scene data representing the scene from a viewing region. The three dimensional scene data may e.g. be images and depth maps captured from capture positions within the viewing region. A movement processor (105) receives motion data, such as head or eye tracking data, for a user and determines an observer viewing position and an observer viewing orientation from the motion data. A change processor (109) determines an orientation change measure for the observer viewing orientation and an adapter (111) is arranged to reduce a distance from the observer viewing position relative to the viewing region in response to the orientation change measure. An image generator (103) generates view images for the observer viewing position and the observer viewing orientation from the scene data.

Provided is a method for creating a virtual reality content, storing the virtual reality content in a transmission buffer, and after that, managing the transmission buffer. A server creates the virtual reality content based on user's motion information, stores the virtual reality content in the transmission buffer and is allowed to modify the virtual reality content stored in the transmission buffer based on subsequently received user's motion information, so that the most recent user's motion information can be appropriately reflected in the virtual reality content. It is possible to provide a more immersive virtual reality service.

Described herein are sensing methods, sensor systems, and non-transitory, computer-readable, storage media having programs for long-duration, continuous monitoring of flying objects during the day or the night and regardless of weather conditions. The methods and systems are computationally efficient and can provide compact, three-dimensional representations of motion from the observed object. A 3D track of the flying object can be generated from a point-matched pair of stereo composite motion track images and not directly from the videos, wherein each composite motion track image is based on a composite of a plurality of video frames composited in part according to video frame numbers.