Dynamic tracking methods for an in-vivo three-dimensional key point and an in-vivo three-dimensional curve can include mapping a first local region to a first local point cloud and mapping a second local region to a second local point cloud according to a mapping relation between an endoscopic image and the point clouds; determining a first three-dimensional key point of a first two-dimensional key point on the first local point cloud, and acquiring a second three-dimensional key point on the second local point cloud through a coordinate transformation; and mapping the second three-dimensional key point back to the second local region, so as to acquire a second two-dimensional key point from a next image; and acquiring two-dimensional coordinates of a tracked key point by minimizing a preset optimization function in combination with an initial two-dimensional key point, and finally acquiring corresponding three-dimensional coordinates.

The present invention discloses a method and apparatus for quality assurance of an automobile component using a marker. The method comprises (a) a step in which an image photographing unit photographs a fully assembled component to which a marker having a predetermined shape is already attached by being driven according to an operation of a terminal having a photographing function; (b) a step in which an image pre-processing unit corrects the basic image using the marker and outputs, after receiving the photographed image, using an image processing function, and specifies the dimensions of the fully assembled components according to the difference in size and shape of the components fully assembled with the markers; (c) a step in which a distance and step measurement unit measures a distance and a step of the component by receiving the corrected basic image and performs a measuring part measurement algorithm; (d) a step in which a measurement data storage unit receives and stores measurement data on the measured distances and steps; and (e) a step in which an image output device receives and displays the corrected basic image and the measurement data, wherein the measuring part measurement algorithm calculates an absolute length of the vertical line with respect to an absolute length of the marker by using an intersection between a vertical line based on a measurement reference point of the measuring part of the component in the corrected basic image and a relative reference point of the component to measure the distance and step of the component.

Methods, apparatus, systems, and articles of manufacture for real-time interactive anamorphosis projection via face detection and tracking are disclosed. An example system includes a sensor to capture an image of a face of a user. An augmented reality controller is to access the image from the sensor, determine a position of the face of the user relative to a display surface, and apply a perspective correction to an anamorphic camera representing a vantage point of the active user. A user application is to generate a scene based on the position of the anamorphic camera. A display is to present, at the display surface, the scene based on the vantage point of the active user.

Embodiments of this application disclose a camera attitude tracking method and apparatus, a device, and a system in the field of augmented reality (AR). The method includes receiving, by a second device with a camera, an initial image and an initial attitude parameter that are transmitted by a first device; obtaining, by the second device, a second image acquired by the camera; obtaining, by the second device, a camera attitude variation of the second image relative to the initial image; and obtaining, by the second device, according to the initial attitude parameter and the camera attitude variation, a second camera attitude parameter, the second camera attitude parameter corresponding to the second image.

Techniques are disclosed for deforming an image using Bezier transformation. The image is divided in a plurality of sections. Each section represents a corresponding Bezier patch. Each section comprises a multiple control points for Bezier transformation, with corner control points of the sections forming anchor points. The deformation of the image is performed by selecting multiple anchor points, and interacting with the selected anchor points. A bounding box that includes the selected anchor points is displayed. Translating, rotating, and/or scaling the selected anchor points based on user input relative to the bounding box results in corresponding Bezier transformation of portion of the image within the bounding box. Thus, instead of having to interact with one control point at a time to deform the image, the desired deformation is achieved by selecting multiple anchor points, and applying the Bezier deformation to the whole bounding box defined by the selected anchor points.

An image photographing method is provided, including: based on a photographing instruction, selecting at least one focus in a quadrangular image, and photographing at least one initial image based on the at least one focus, where the quadrangular image includes a first pair of opposite sides and a second pair of opposite sides, an included angle between the opposite sides of the first pair of opposite sides is less than that of the second pair of opposite sides, a first side is a shorter side of the first pair of opposite sides, the at least one focus includes a first focus, and the first focus is in the quadrangular image and in a partial region including the first side; adjusting a quadrangular image to a rectangular image; and obtaining a final image and outputting the final image.

The present technology relates to an image generating device, an image generating method, and a program which are capable of calling attention of a user quickly. An integrating unit integrates a first image and a second image and generates an integrated image. A superimposition executing unit causes an alert mark to be superimposed on the integrated image and generates a superimposed image in a case in which an object shown in the second image is positioned on a farther side than an object shown in the first image. The present technology can be applied to, for example, a Camera Monitor System (CMS) which provides, for example, an image corresponding to an image observed by a side mirror or a rearview mirror or the like.

A graphical object processor has a single filter. The filter includes a program for constructing a pipeline consisted of a plurality of stages based on a print ticket. In one or more of the plurality of stages, a content box of print-target data is modified. When the content box is modified, commands respectively indicating affine transformation matrices are generated. The commands are pushed into a command stack. The pushed commands are used for modification of a visual element. Specifically, the affine transformation matrices are multiplied and thereby an integrated transformation matrix is generated. The visual element is modified by multiplying an affine transformation matrix of the visual element by the integrated transformation matrix.

A computer implemented method for generating a one-to-one mapping between a first spatial point set and a second spatial point set in nD comprising receiving a first and a second spatial point sets in nD; generating one or more MatchPairs between the first and the second point sets; computing local distance measures for the MatchPairs; converting the local distance measures to weights; computing compatibility between each pair of the MatchPairs; constructing an undirected graph with its nodes corresponding to the MatchPairs, its edges representing the compatibilities, and its graph vertices assigned the weights; computing a maximum-weight clique of the graph; and merging the maximum-weight clique to generate the one-to-one mapping.

A device and computer implemented method for digital image content recognition. The method includes determining, depending on a digital image, a first candidate class for the content of the digital image by a baseline model neural network comprising a first feature extractor and a first classifier for classifying digital images; determining a second candidate class for the content of the digital image by a prototypical neural network comprising a second feature extractor and a second classifier for classifying digital images, classifying the content of the digital image into either the first candidate class or the second candidate class depending on the result of a comparison of a first confidence score for the first candidate class to a threshold or of a comparison of a first confidence score for the first candidate class to a second confidence score for the second candidate class.