A method for environmental acquisition for acquiring the surrounding environment of a vehicle. Using a plurality of cameras and/or sensor devices, from at least two positions, images of the surrounding environment are produced, and on the basis of the images a free surface, as well as a contour bounding the free surface, are ascertained. Separately for each image and the contour determined on the basis of this image, for a multiplicity of points along the contour, feature vectors are calculated and entered into a one-dimensional array. Through matching of the one-dimensional arrays, correspondences are sought for which the three-dimensional position is subsequently ascertained by triangulation. A computing unit for carrying out at least individual method steps of the method is also described.

A distance measurement method is provided. The distance measurement method includes obtaining an image of a target device, the image of the target device including a target object of a first color and a background object of a second color, the first color being different from the second color; processing the image of the target device to obtain a processed image, the processed image including a processed target object of a third color and a processed background object of a fourth color; detecting a contour of the processed target object of the third color; calculating an area encircled by the contour; and calculating a distance between a camera and the target device upon determination of the area encircled by the contour.

A distance measurement method is provided. The distance measurement method includes obtaining an image of a target device, the image of the target device including a target object of a first color and a background object of a second color, the first color being different from the second color; processing the image of the target device to obtain a processed image, the processed image including a processed target object of a third color and a processed background object of a fourth color; detecting a contour of the processed target object of the third color; calculating an area encircled by the contour; and calculating a distance between a camera and the target device upon determination of the area encircled by the contour.

Image processing apparatus responsive to successive groups of images of an object captured at the same time by two or more spaced apart image capturing devices and to depth information indicating a three-dimensional location of the object relative to at least one distance measuring device includes: a frame selecting unit configured to select a set of the successive image groups; a model generating unit configured to generate a three dimensional model, for each image group in the set of image groups, from images captured at the same time by the two or more spaced apart image capturing devices and from the depth information, and to map a texture to the generated three dimensional model; and a composition unit configured to generate a stroboscopic image, with respect to a stroboscopic image viewpoint, by superposing the three dimensional models generated by the model generating unit on a predetermined background.

A method to reconstruct an environment is provided. The method makes available to a wide variety of XR applications fresh and accurate 3D reconstruction data of environments with low processing time and low usage of computational resources and storage spaces. The 3D reconstruction data are structured in a way to be efficiently shared between users for multi-user experiences. The method includes obtaining plane segments of an environment, identifying surface planes of the environment by, for example, filtering and grouping the plane segments or ad hoc selection of the plane segments by a user, and inferring corner points of the environment based on the surface planes. The corner points are used to build a 3D representation of the environment when an XR application requires.

A method to reconstruct an environment is provided. The method makes available to a wide variety of XR applications fresh and accurate 3D reconstruction data of environments with low processing time and low usage of computational resources and storage spaces. The 3D reconstruction data are structured in a way to be efficiently shared between users for multi-user experiences. The method includes obtaining plane segments of an environment, identifying surface planes of the environment by, for example, filtering and grouping the plane segments or ad hoc selection of the plane segments by a user, and inferring corner points of the environment based on the surface planes. The corner points are used to build a 3D representation of the environment when an XR application requires.

The mesh tracking described herein involves mesh tracking on 3D face models. In contrast to existing mesh tracking algorithms which generally require user intervention and manipulation, the mesh tracking algorithm is fully automatic once a template mesh is provided. In addition, an eye and mouth boundary detection algorithm is able to better reconstruct the shape of eyes and mouths.

The mesh tracking described herein involves mesh tracking on 3D face models. In contrast to existing mesh tracking algorithms which generally require user intervention and manipulation, the mesh tracking algorithm is fully automatic once a template mesh is provided. In addition, an eye and mouth boundary detection algorithm is able to better reconstruct the shape of eyes and mouths.

A method to reconstruct an environment is provided. The method makes available to a wide variety of XR applications fresh and accurate 3D reconstruction data of environments with low processing time and low usage of computational resources and storage spaces. The 3D reconstruction data are structured in a way to be efficiently shared between users for multi-user experiences. The method includes obtaining plane segments of an environment, identifying surface planes of the environment by, for example, filtering and grouping the plane segments or ad hoc selection of the plane segments by a user, and inferring corner points of the environment based on the surface planes. The corner points are used to build a 3D representation of the environment when an XR application requires.

A method to reconstruct an environment is provided. The method makes available to a wide variety of XR applications fresh and accurate 3D reconstruction data of environments with low processing time and low usage of computational resources and storage spaces. The 3D reconstruction data are structured in a way to be efficiently shared between users for multi-user experiences. The method includes obtaining plane segments of an environment, identifying surface planes of the environment by, for example, filtering and grouping the plane segments or ad hoc selection of the plane segments by a user, and inferring corner points of the environment based on the surface planes. The corner points are used to build a 3D representation of the environment when an XR application requires.