Abstract: During pre-processing, a 3D model of the object is rendered for various poses by arranging virtual point light sources around the lens of a virtual camera. The shadows are used to obtain oriented depth edges of the object illuminated from multiple directions. The oriented depth edges are stored in a database. A camera acquires images of the scene by casting shadows onto the scene from different directions. The scene can include one or more objects arranged in arbitrary poses with respect to each other. The poses of the objects are determined by comparing the oriented depth edges obtained from the acquired images to the oriented depth edges stored in the database. The comparing evaluates, at each pixel, a cost function based on chamfer matching, which can be speed up using downhill simplex optimization.

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: During pre-processing, a 3D model of the object is rendered for various poses by arranging virtual point light sources around the lens of a virtual camera. The shadows are used to obtain oriented depth edges of the object illuminated from multiple directions. The oriented depth edges are stored in a database. A camera acquires images of the scene by casting shadows onto the scene from different directions. The scene can include one or more objects arranged in arbitrary poses with respect to each other. The poses of the objects are determined by comparing the oriented depth edges obtained from the acquired images to the oriented depth edges stored in the database. The comparing evaluates, at each pixel, a cost function based on chamfer matching, which can be speed up using downhill simplex optimization.

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.