Abstract: A plenoptic imaging system includes imaging optics, a microlens array and a sensor array. A method for generating a preview image of a plenoptic image captured by the plenoptic imaging system includes the following. A plenoptic image of an object captured by the plenoptic imaging system is accessed. The plenoptic image includes many superpixels. Each superpixel includes many subpixels. For each superpixel, a set of reliable subpixels is selected based at least in part on vignetting of the subpixels. A preview image is generated from the sets of reliable subpixels. The preview image includes pixels corresponding to the superpixels. The pixels in the preview image are generated from the set of reliable subpixels for the corresponding superpixels.

Abstract: A plenoptic imaging system includes imaging optics, a microlens array and a sensor array. A method for generating a preview image of a plenoptic image captured by the plenoptic imaging system includes the following. A plenoptic image of an object captured by the plenoptic imaging system is accessed. The plenoptic image includes many superpixels. Each superpixel includes many subpixels. For each superpixel, a set of reliable subpixels is selected based at least in part on vignetting of the subpixels. A preview image is generated from the sets of reliable subpixels. The preview image includes pixels corresponding to the superpixels. The pixels in the preview image are generated from the set of reliable subpixels for the corresponding superpixels.

Abstract: A three-dimensional image of the eardrum is automatically registered. In one aspect, a three-dimensional image (e.g., depth map) of an eardrum is produced from four-dimensional light field data captured by a light field otoscope. The three-dimensional image is registered according to a predefined standard form. The eardrum is then classified based on the registered three-dimensional image. Registration may include compensation for out-of-plane rotation (tilt), for in-plane rotation, for center location, for translation, and/or for scaling.

Abstract: Eardrums are automatically classified based on a feature set from a three-dimensional image of the eardrum, such as might be derived from a plenoptic image captured by a light field otoscope. In one aspect, a grid is overlaid onto the three-dimensional image of the eardrum. The grid partitions the three-dimensional image into cells. One or more descriptors are calculated for each of the cells, and the feature set includes the calculated descriptors. Examples of descriptors include various quantities relating to the depth and/or curvature of the eardrum. In another aspect, isocontour lines (of constant depth) are calculated for the three-dimensional image of the eardrum. One or more descriptors are calculated for the isocontour lines, and the feature set includes the calculated descriptors. Examples of descriptors include various quantities characterizing the isocontour lines.

Abstract: A system includes cameras; a rotating stage, which has an axis of rotation; one or more computer-readable media; and one or more processors that are coupled to the one or more computer-readable media, the rotating state, and the cameras. Also, the one or more processors are configured to cause the system to control the cameras to capture respective images of a calibration target in a first pose, wherein the calibration target is mounted on the rotating stage; control the rotating stage to rotate through a predetermined angular increment to a second pose; control the cameras to capture respective images of the calibration target in the second pose; and calculate a transformation between two of the cameras based on the respective images of the calibration target in the first pose, on the respective images of the calibration target in the second pose, and on the predetermined angular increment.

Abstract: 3D shape reconstruction of objects including specular objects in which structured light patterns are projected toward an object which reflects the patterns onto multiple layers of EGlass arranged in spaced-apart relation with each other while each layer is in turn controlled to be in the diffuse mode with all others being in the transparent mode. Images are captured of the structured light pattern as reflected onto the EGlass layers by the mirror-like surface of the specular object. By projecting multiple different patterns, such as multiple different Gray code patterns, and by sequencing through each EGlass layer for each pattern, the 3D shape of the entirety of the visible surface of the object can be reconstructed by analysis of captured images of the distorted reflections of the patterns by the surface of the object. Embodiments are also described which can be used without reconfiguration for surface reconstruction of the shape of diffuse objects.

Abstract: Shape measurement of a specular object even in the presence of multiple intra-object reflections such as those at concave regions of the object. Silhouettes of the object are extracted, by positioning the object between a camera and a background. A visual hull of the object is reconstructed based on the extracted silhouettes, such as by image capture of shadows of the object projected onto a screen, and image capture of reflections by the surface of the object of coded patterns onto the screen. The visual hull is used to distinguish between direct (single) reflections of the coded patterns at the surface of the object and multiple reflections. Only the direct (single) reflections are used to triangulate camera rays and light rays onto the surface of the object, with multiple reflections being excluded. The 3D surface shape may be derived by voxel carving of the visual hull, in which voxels along the light path of direct reflections are eliminated.

Abstract: 3D shape reconstruction of objects including specular objects in which structured light patterns are projected toward an object which reflects the patterns onto multiple layers of EGlass arranged in spaced-apart relation with each other while each layer is in turn controlled to be in the diffuse mode with all others being in the transparent mode. Images are captured of the structured light pattern as reflected onto the EGlass layers by the mirror-like surface of the specular object. By projecting multiple different patterns, such as multiple different Gray code patterns, and by sequencing through each EGlass layer for each pattern, the 3D shape of the entirety of the visible surface of the object can be reconstructed by analysis of captured images of the distorted reflections of the patterns by the surface of the object. Embodiments are also described which can be used without reconfiguration for surface reconstruction of the shape of diffuse objects.

Abstract: 3D shape reconstruction of glossy objects includes separation of diffuse and specular components of reflection from the object. Multiple layers of E-glass arranged in spaced-apart relation with each other, together with a camera for capturing images of reflected light. A first polarizer is positioned to polarize incident light before it reaches the object and a second polarizer is configured as an analyzer to analyze the light reflected from the object. The degree of polarization is varied. Images are captured of a structured light pattern as reflected in both diffuse and specular reflection the surface of the glossy object. A diffuse component of reflection is extracted by using the captured images of the deformed patterns, and a specular component of reflection is extracted by using the diffuse component of reflection and the captured images under polarized illumination. Depth of the surface of the object is estimated by fusing the diffuse component and the specular component.

Abstract: Devices, systems, and methods for estimating blur in an image obtain an image, identify pixels in the image that have intensity values that equal or exceed a first intensity threshold in a first color channel, and identify a trajectory based on the pixels in the image that have intensity values that exceed the first intensity threshold in the first color channel. Also, the devices, systems, and methods identify multiple instances of the trajectory in the image, identify an instance of the trajectory that includes pixels that have intensity values that do not equal or exceed a second intensity threshold in a second color channel, and generate a blur kernel based on the intensity values in the second color channel of the pixels in the instance of the trajectory.

Abstract: A system includes cameras; a rotating stage, which has an axis of rotation; one or more computer-readable media; and one or more processors that are coupled to the one or more computer-readable media, the rotating state, and the cameras. Also, the one or more processors are configured to cause the system to control the cameras to capture respective images of a calibration target in a first pose, wherein the calibration target is mounted on the rotating stage; control the rotating stage to rotate through a predetermined angular increment to a second pose; control the cameras to capture respective images of the calibration target in the second pose; and calculate a transformation between two of the cameras based on the respective images of the calibration target in the first pose, on the respective images of the calibration target in the second pose, and on the predetermined angular increment.

Abstract: Recovery of local curvature and surface shape of an object having a specular component of reflection such as a mirror-like or specular object. The object is illuminated by a rainbow-like ordered spectrum of spatially distributed light whose wavelength varies in accordance with angle, and a spectral image is captured of the object. Local curvature is estimated for a point on the object based on spectral width at a wavelength peak of light reflected from the point, with a relatively wider width corresponding to a locally convex curvature and a relatively narrow width corresponding to a locally concave curvature. Surface shape information is recovered using the captured image based on a set relationship, obtained by calibration, by which wavelength of the ordered spectrum varies in accordance with angle. Physical and/or graphical replication of the object is informed by the recovered local curvature and surface shape.

Abstract: Devices, systems, and methods for estimating blur in an image obtain an image, identify pixels in the image that have intensity values that equal or exceed a first intensity threshold in a first color channel, and identify a trajectory based on the pixels in the image that have intensity values that exceed the first intensity threshold in the first color channel. Also, the devices, systems, and methods identify multiple instances of the trajectory in the image, identify an instance of the trajectory that includes pixels that have intensity values that do not equal or exceed a second intensity threshold in a second color channel, and generate a blur kernel based on the intensity values in the second color channel of the pixels in the instance of the trajectory.