Abstract: A single camera acquires an input image of a scene as observed in an array of spheres, wherein pixels in the input image corresponding to each sphere form a sphere image. A set of virtual cameras are defined for each sphere on a line joining a center of the sphere and a center of projection of the camera, wherein each virtual camera has a different virtual viewpoint and an associated cone of rays, appearing as a circle of pixels on its virtual image plane. A projective texture mapping of each sphere image is applied to all of the virtual cameras on the virtual image plane to produce a virtual camera image comprising circle of pixels. Each virtual camera image for each sphere is then projected to a refocusing geometry using a refocus viewpoint to produce a wide-angle lightfield view, which are averaged to produce a refocused wide-angle image.

Abstract: A method estimates a 3D pose of a 3D specular object in an environment. In a preprocessing step, a set of pairs of 2D reference images are generated using a 3D model of the object, and a set of poses of the object, wherein each pair of reference images is associated with one of the poses. Then, a pair of 2D input images are acquired of the object. A rough 3D pose of the object is estimated by comparing features in the pair of 2D input images and the features in each pair of 2D reference images using a rough cost function. The rough estimate is optionally refined using a fine cost function.

Abstract: Embodiments of invention disclose a system and a method for increasing a temporal resolution of a substantially periodic signal. The method acquires a signal as an input sequence of frames having a first temporal resolution, wherein the signal is a substantially periodic signal, wherein the frames in the input sequence of frames are encoded according to an encoded pattern; and transforms the input sequence of frames into an output sequence of frames having a second temporal resolution, such that the second temporal resolution is greater than the first temporal resolution, wherein the transforming is based on a sparsity of the signal in Fourier domain.

Abstract: A single camera acquires an input image of a scene as observed in an array of spheres, wherein pixels in the input image corresponding to each sphere form a sphere image. A set of virtual cameras are defined for each sphere on a line joining a center of the sphere and a center of projection of the camera, wherein each virtual camera has a different virtual viewpoint and an associated cone of rays, appearing as a circle of pixels on its virtual image plane. A projective texture mapping of each sphere image is applied to all of the virtual cameras on the virtual image plane to produce a virtual camera image comprising circle of pixels. Each virtual camera image for each sphere is then projected to a refocusing geometry using a refocus viewpoint to produce a wide-angle lightfield view, which are averaged to produce a refocused wide-angle image.

Abstract: Embodiments of invention disclose a system and a method for increasing a temporal resolution of a substantially periodic signal. The method acquires a signal as an input sequence of frames having a first temporal resolution, wherein the signal is a substantially periodic signal, wherein the frames in the input sequence of frames are encoded according to an encoded pattern; and transforms the input sequence of frames into an output sequence of frames having a second temporal resolution, such that the second temporal resolution is greater than the first temporal resolution, wherein the transforming is based on a sparsity of the signal in Fourier domain.

Abstract: A method estimates a 3D pose of a 3D specular object in an environment. In a preprocessing step, a set of pairs of 2D reference images are generated using a 3D model of the object, and a set of poses of the object, wherein each pair of reference images is associated with one of the poses. Then, a pair of 2D input images are acquired of the object. A rough 3D pose of the object is estimated by comparing features in the pair of 2D input images and the features in each pair of 2D reference images using a rough cost function. The rough estimate is optionally refined using a fine cost function.