Systems and methods are disclosed for generating a scaled reconstruction for a consumer product. One method includes receiving digital input comprising a calibration target and an object; defining a three-dimensional coordinate system; positioning the calibration target in the three-dimensional coordinate system; based on the digital input, aligning the object to the calibration target in the three-dimensional coordinate system; and generating a scaled reconstruction of the object based on the alignment of the object to the calibration target in the three-dimensional coordinate system.

A computer-implemented method for learning an autoencoder notably is provided. The method includes obtaining a dataset of images. Each image includes a respective object representation. The method also includes learning the autoencoder based on the dataset. The learning includes minimization of a reconstruction loss. The reconstruction loss includes a term that penalizes a distance for each respective image. The penalized distance is between the result of applying the autoencoder to the respective image and the set of results of applying at least part of a group of transformations to the object representation of the respective image. Such a method provides an improved solution to learn an autoencoder.

The self-localization device includes: an acquisition unit configured to acquire a sight image from a camera which is mounted in a mobile object; an estimation unit configured to perform a self-localization process of estimating a position and a posture of the mobile object in a world coordinate system on the basis of positions of feature points in the sight image and a map on which positions of a plurality of feature points in the world coordinate system are recorded; and a registration unit configured to register the sight image as a key frame for adding a new feature point included in the sight image to the map. The registration unit is configured to register the sight image as the key frame when movement of the mobile object satisfies a condition which is prescribed for at least one of the position and the posture of the mobile object.

Embodiments include a system and a method for determining a geographic location corresponding to pixels in a scan. For a scan of an area including a plurality of pixels, measurements of at least one physical property may be received. An embodiment may include identifying in the scan at least a first pixel and a second pixel corresponding to known at least a first and a second geographical locations; creating a set of pixel values vectors, for each pixel values vector calculating a correlation factor between the pixel values vector and a vector that includes the measurements; selecting a pixel values vector, from the set of pixel values vectors, for which a correlation factor higher than a threshold value was calculated; and determining the actual geographic location of the area represented by each pixel in the selected pixel values vector based on the known geographic locations.

Disclosed is a system for performing User Interface (UI) verification of a Device Under Test (DUT). Before performing the UI verification, a set of corner markers is positioned at corners of a display frame associated to the DUT. Once the set of corner markers are positioned, an image receiving module receives a DUT image, captured by an image capturing unit, of the UI pertaining to a DUT. A skew correction module for correcting orientation of the DUT image by determining an orientation correction factor. A file configuration module for storing the orientation correction factor in a pre-configuration file when the DUT image is occupying the content greater than the predefined threshold percentage. In one aspect, the orientation correction factor may be referred while testing a UI of the DUT.

A system and method of assisting a treatment procedure is provided, the method comprising the steps of determining a 3-D intervention vector in relation to an inner body structure of a body of interest based on a 3-D x-ray image, determining a 3-D position of an entry point on an outer surface of the body of interest based on the intervention vector, comparing the position and/or orientation of the inner body structure in the 3-D x-ray image with the position and/or orientation of the inner body structure in an additional 2-D x-ray image being generated transverse to the intervention vector, correcting the 3-D position of the entry point on the outer surface of the body of interest based on a deviation detected in the comparing step.

An image processing apparatus in which identification of a corresponding target point between images is easily performed, and physically appropriate registration can be performed by using the identification is provided. The image processing apparatus obtains coordinate transformation for respectively transforming a first image and a second image obtained by imaging an object to a first transformed image and a second transformed image, obtains correspondence information that serves as information of a corresponding point included in each of the first transformed image and the second transformed image, respectively transforms the correspondence information to positions in the first image and the second image, and obtains deformation transformation for performing registration of the first image and the second image on the basis of information of the corresponding points in the first image and the second image.

A map generation system, method and computer program product are provided to generate a shadow layer from a raster image that accurately represents the shadows of one or more buildings. In the context of a map generation system, the map generation system extracts pixel values from a raster image of one or more buildings and processes the pixel values so as to retain pixel values within a predefined range while eliminating other pixel values. The pixel values that are retained represent a shadow. The map generation system also modifies the a representation of the shadow by modifying the pixel values of respective pixels so as to have a shape corresponding to the shape of the one or more buildings. The map generation system causes presentation or storage of the building layer representing the one or more buildings and a shadow layer representing the shadow.

Various examples are provided for fingerprint distortion rectification. In one example, a method includes selecting a geometrically distorted fingerprint sample and generating a rectified fingerprint sample by rectifying geometric distortions from the geometrically distorted fingerprint sample by application of an estimated distortion field determined by a deep convolutional neural network (DCNN) trained previously on a database of synthetic, geometrically distorted fingerprint samples. In another example, a system includes a distortion rectification application that, when executed by processing circuitry, causes the processing circuitry to identify distortion parameters associated with a distorted fingerprint, the distortion parameters estimated from the distorted fingerprint by a DCNN and generate a rectified fingerprint from the distorted fingerprint, the rectified fingerprint generated using an inverse geometric transformation based upon the identified distortion parameters

Embodiments disclose systems and methods that aid in screening, diagnosis and/or monitoring of medical conditions. The systems and methods may allow, for example, for automated identification and localization of lesions and other anatomical structures from medical data obtained from medical imaging devices, computation of image-based biomarkers including quantification of dynamics of lesions, and/or integration with telemedicine services, programs, or software.