Provided is a control device including a control unit that calculates a first positional relationship between an eye of an observer observing an object displayed on a display unit and a first point in a master-side three-dimensional coordinate system, and controls an imaging unit that images the object so that a second positional relationship between the imaging unit and a second point corresponding to the first point in a slave-side three-dimensional coordinate system corresponds to the first positional relationship.

Provided is a control device including a control unit that calculates a first positional relationship between an eye of an observer observing an object displayed on a display unit and a first point in a master-side three-dimensional coordinate system, and controls an imaging unit that images the object so that a second positional relationship between the imaging unit and a second point corresponding to the first point in a slave-side three-dimensional coordinate system corresponds to the first positional relationship.

Disclosed are an apparatus and a method for generating an image for generation of a 3D panorama image. A method for generating a 3D panorama image in an image generating apparatus comprises the steps of: receiving an input of a plurality of 2D images and a plurality of depth maps corresponding to the plurality of 2D images; setting a left-eye image area and a right-eye image area for each of the plurality of 2D images on the basis of the plurality of depth maps; and synthesizing images of each of the left-eye image areas that are set in the plurality of 2D images to thereby generate a left-eye panorama image and synthesizing images of each of the right-eye image areas that are set in the plurality of 2D images to thereby generate a right-eye panorama image. Accordingly, the image generating apparatus can generate a 3D panorama image without distortion on the basis of a plurality of 2D images.

An endoscopic image processing apparatus is configured to create a three-dimensional shape model of an object by performing processing on an endoscopic image group of an inside of the object, and includes a processor. The processor estimates a self-position of the image pickup device based on the endoscopic image group, calculates a first displacement amount corresponding to a displacement amount of the image pickup device based on an estimation result of the self-position of the image pickup device obtained by the estimation, calculates a second displacement amount corresponding to a displacement amount in a direction parallel to a longitudinal axis direction of the insertion portion, based on a detection signal outputted from an insertion/removal state detection device that detects an insertion/removal state of an insertion portion inserted into the object, and generates scale information in which the first displacement amount and the second displacement amount are associated with each other.

An endoscopic image processing apparatus is configured to create a three-dimensional shape model of an object by performing processing on an endoscopic image group of an inside of the object, and includes a processor. The processor estimates a self-position of the image pickup device based on the endoscopic image group, calculates a first displacement amount corresponding to a displacement amount of the image pickup device based on an estimation result of the self-position of the image pickup device obtained by the estimation, calculates a second displacement amount corresponding to a displacement amount in a direction parallel to a longitudinal axis direction of the insertion portion, based on a detection signal outputted from an insertion/removal state detection device that detects an insertion/removal state of an insertion portion inserted into the object, and generates scale information in which the first displacement amount and the second displacement amount are associated with each other.

A method for ascertaining an image of the surroundings of a vehicle. The method includes reading in first image data and at least second image data, the first image data representing image data of a first image recording area of a camera in or on a vehicle and the second image data representing image data from a second image recording area of the camera differing from the first image recording area, and the second image data having been recorded chronologically after the first image data. The method further includes processing the second image data using a vehicle parameter and/or driving parameter, to obtain processed second image data. Finally, the method includes combining the first image data with the processed second image data to obtain the image of the surroundings of the vehicle.

A smartphone may be freely moved in three dimensions as it captures a stream of images of an object. Multiple image frames may be captured in different orientations and distances from the object and combined into a composite image representing an three-dimensional image of the object. The image frames may be formed into the composite image based on representing features of each image frame as a set of points in a three dimensional depth map. Coordinates of the points in the depth map may be estimated with a level of certainty. The level of certainty may be used to determine which points are included in the composite image. The selected points may be smoothed and a mesh model may be formed by creating a convex hull of the selected points. The mesh model and associated texture information may be used to render a three-dimensional representation of the object on a two-dimensional display. Additional techniques include processing and formatting of the three-dimensional representation data to be printed by a three-dimensional printer so a three-dimensional model of the object may be formed.

A smartphone may be freely moved in three dimensions as it captures a stream of images of an object. Multiple image frames may be captured in different orientations and distances from the object and combined into a composite image representing an three-dimensional image of the object. The image frames may be formed into the composite image based on representing features of each image frame as a set of points in a three dimensional depth map. Coordinates of the points in the depth map may be estimated with a level of certainty. The level of certainty may be used to determine which points are included in the composite image. The selected points may be smoothed and a mesh model may be formed by creating a convex hull of the selected points. The mesh model and associated texture information may be used to render a three-dimensional representation of the object on a two-dimensional display. Additional techniques include processing and formatting of the three-dimensional representation data to be printed by a three-dimensional printer so a three-dimensional model of the object may be formed.

A road surface detection device according to an embodiment includes an image acquisition unit that acquires captured image data output from a stereo camera that captures an imaging area including a road surface on which a vehicle travels, a three-dimensional model generation unit that generates a three-dimensional model of the imaging area including a surface shape of the road surface from a viewpoint of the stereo camera based on the captured image data, and a correction unit that estimates a plane from the three-dimensional model, and corrects the three-dimensional model so as to match an orientation of a normal vector of the plane and a height position of the plane with respect to the stereo camera with a correct value of an orientation of a normal vector of the road surface and a correct value of a height position of the road surface with respect to the stereo camera, respectively.

A road surface detection device according to an embodiment includes an image acquisition unit that acquires captured image data output from a stereo camera that captures an imaging area including a road surface on which a vehicle travels, a three-dimensional model generation unit that generates a three-dimensional model of the imaging area including a surface shape of the road surface from a viewpoint of the stereo camera based on the captured image data, and a correction unit that estimates a plane from the three-dimensional model, and corrects the three-dimensional model so as to match an orientation of a normal vector of the plane and a height position of the plane with respect to the stereo camera with a correct value of an orientation of a normal vector of the road surface and a correct value of a height position of the road surface with respect to the stereo camera, respectively.