An apparatus comprising an interface, a structured light projector and a processor. The interface may receive pixel data. The structured light projector may generate a structured light pattern. The processor may process the pixel data arranged as video frames, perform operations using a convolutional neural network to determine a binarization result and an offset value and generate disparity and depth maps in response to the video frames, the structured light pattern, the binarization result, the offset value and a removal of error points. The convolutional neural network may perform a partial block summation to generate a convolution result, compare the convolution result to a speckle value to determine the offset value, generate an adaptive result in response to performing a convolution operation, compare the video frames to the adaptive result to generate the binarization result for the video frames, and remove the error points from the binarization result.

An apparatus comprising an interface, a structured light projector and a processor. The interface may receive pixel data. The structured light projector may generate a structured light pattern. The processor may process the pixel data arranged as video frames, perform operations using a convolutional neural network to determine a binarization result and an offset value and generate disparity and depth maps in response to the video frames, the structured light pattern, the binarization result, the offset value and a removal of error points. The convolutional neural network may perform a partial block summation to generate a convolution result, compare the convolution result to a speckle value to determine the offset value, generate an adaptive result in response to performing a convolution operation, compare the video frames to the adaptive result to generate the binarization result for the video frames, and remove the error points from the binarization result.

An imaging unit 20 has a configuration in which an identical polarization pixel block made up of a plurality of pixels with an identical polarization direction is provided for each of a plurality of polarization directions and pixels of respective predetermined colors are provided in the identical polarization pixel block. A correction processing unit 31 performs correction processing such as white balance correction on a polarized image generated by the imaging unit 20. A polarized image processing unit 32 separates or extracts a reflection component using the polarized image after the correction processing. By using a polarized image of the separated or extracted reflection component, for example, it is possible to generate normal line information with high accuracy.

A detection device includes: a detector that detects an object from a first viewpoint; an information calculator that calculates first model information including shape information on the object from the first viewpoint by using detection results of the detector; a light source calculator that calculates light source information on the light source by using a first taken image obtained by imaging a space including a light source that irradiates the object with illumination light and including the object; and a position calculator that calculates a positional relation between the first viewpoint and the object by using the light source information as information used to integrate the first model information and second model information including shape information obtained by detecting the object from a second viewpoint different from the first viewpoint.

According to one embodiment, an image processing apparatus includes a buffer and processing circuitry. The buffer stores first and second images capturing an object. The circuitry calculates at least one of a first distance to the object in the first image and a second distance to the object in the second image by using a correction parameter for correcting at least one of influences caused by ambient light, a reflection characteristic of the object, or a color of the object, calculates three-dimensional coordinates of the object on a relative scale by using the first and second images, and calculates three-dimensional coordinates of the object on a real scale based on at least one of the first and second distances, and the three-dimensional coordinates of the object on the relative scale.

A ground material density measurement system is disclosed. The ground material density measurement system may receive a moisture measurement associated with an amount of moisture on a ground surface of a section of ground material. The ground material density measurement system may determine a GPR measurement associated with the section of ground material. The ground material density measurement system may process the GPR measurement based on the moisture measurement to account for the amount of moisture. The ground material density measurement system may provide density information associated with the section of ground material based on the processed GPR measurement.

A ground material density measurement system is disclosed. The ground material density measurement system may receive a moisture measurement associated with an amount of moisture on a ground surface of a section of ground material. The ground material density measurement system may determine a GPR measurement associated with the section of ground material. The ground material density measurement system may process the GPR measurement based on the moisture measurement to account for the amount of moisture. The ground material density measurement system may provide density information associated with the section of ground material based on the processed GPR measurement.

Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

The invention relates to a method for optically measuring an object having a reflective and/or partially reflective surface. According to the invention, by means of a pattern generator (1), a planar pattern (13) is generated which is varied in at least one optical property such that, at least in partial regions (10), a plurality of different points (p) or a plurality of different groups of points are distinguishable from each other. At least parts of the pattern (13) are reflected by a reflective surface (2) of the object (3) as a reflected pattern onto a detector (14) of a camera unit (4), wherein the reflected pattern is converted by the detector (14) into a camera image (9). A connection between points (q) of the camera image (9) and corresponding points (p) of the pattern (13) can be described by means of a correspondence function which is dependent on geometric properties of the reflective surface (2) of the object (3). At least one of the geometric properties of the reflective surface (2) of the object (3) is determined by using differential geometric properties of a transformation given by the correspondence function. The invention furthermore relates to a corresponding system and a corresponding measuring arrangement.