Abstract: A solar energy collection system can include a plurality of heliostats configured to reflect sunlight to a target mounted on a tower. Each of the heliostats can have a heliostat controller configured to control a respective heliostat so that the sunlight reflected therefrom is directed to at least one of a plurality of cameras. The cameras can be oriented to image the heliostat. A second controller can be configured to compute geometry data that defines a geometry of the surface of the heliostat from captured images thereof. The geometry data can designate a plurality of subsections of the surface. The computing by the second controller can include storing data indicating sections of the captured images corresponding to the plurality of subsections of the heliostat. The second controller can also calculate data indicating respective surface normals of each of said subsections of each of said heliostat.

Abstract: A method for iterative derivation of a master image from sampled images of non-identical, at least partially overlapping, regions of a scene. The method includes defining a transformation operator mapping positions within the master image to corresponding positions in the sampled image; a distortion operator simulating a modulation transfer function associated with an imaging sensor from which the sampled image was generated; and a sampling operator for reducing an image from the output resolution to the resolution of the sampled image. For each sampled image the transformation operator, distortion operator and sampling operator are applied to a current master image hypothesis to generate a predicted image A difference image is calculated which has pixel values corresponding to the difference in corresponding pixel values between the sampled image and the predicted image. A back-projection of each of the difference images is performed to generate a correction image for the current master image hypothesis.

Abstract: A method for deriving three-dimensional information progressively from a streaming video sequence.

Abstract: A system and method for generating three-dimensional models of physical objects, includes the steps of providing a plurality of two dimensional images of a physical object, wherein the two-dimensional images are captured from a plurality of viewing angles of the physical object; associating each of the two-dimensional images with a viewing zone, wherein: the viewing zone includes a range of viewing angles of the physical object; and at least one of the viewing zones having a minimum of three shared boundaries; and processing the associated two-dimensional images for each of the viewing zones to generate a three-dimensional local model of the physical object for each of the viewing zones. In another implementation, views are rendered from a visualized model.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: A method for iterative derivation of a master image from sampled images of non-identical, at least partially overlapping, regions of a scene. The method includes defining a transformation operator mapping positions within the master image to corresponding positions in the sampled image; a distortion operator simulating a modulation transfer function associated with an imaging sensor from which the sampled image was generated; and a sampling operator for reducing an image from the output resolution to the resolution of the sampled image. For each sampled image the transformation operator, distortion operator and sampling operator are applied to a current master image hypothesis to generate a predicted image A difference image is calculated which has pixel values corresponding to the difference in corresponding pixel values between the sampled image and the predicted image. A back-projection of each of the difference images is performed to generate a correction image for the current master image hypothesis.

Abstract: In a system for transmitting a three-dimensional (3-D) digital image over a communication network, in response to a client computer generating a request for interaction with a 3-D image stored on an image storage device, a server computer performs two-dimensional sub-band transform decompositions in x-axis and y-axis directions upon the 3-D image, performs a one-dimensional sub-band transform decomposition in a z-axis direction upon a portion of the two-dimensionally transform-decomposed digital image, and progressively transmits to the client computer data representing a region of interest specified in the client request.

Abstract: A method for deriving three-dimensional information progressively from a streaming video sequence.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: A lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging client generates and sends a ROI request list to the imaging server. The request list can be ordered according to the particular progressive mode selected (e.g., progressive by quality, resolution or spatial order). The imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests in near real time. When a ROI request arrives at the server, a progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: Disclosed is a lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the full image. When a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.

Abstract: In a system for transmitting a three-dimensional (3-D) digital image over a communication network, in response to a client computer generating a request for interaction with a 3-D image stored on an image storage device, a server computer performs two-dimensional sub-band transform decompositions in x-axis and y-axis directions upon the 3-D image, performs a one-dimensional sub-band transform decomposition in a z-axis direction upon a portion of the two-dimensionally transform-decomposed digital image, and progressively transmits to the client computer data representing a region of interest specified in the client request.

Abstract: Disclosed is a lossless image streaming system for the transmission of images over a communication network. The system eliminates the necessity to store a compressed version of the original image, by losslessly streaming ROI data using the original stored image. The imaging system of the present invention also avoids the computationally intensive task of compression of the fall image. When a user wishes to interact with a remote image, the imaging server performs a fast preprocessing step in near real time after which it can respond to any ROI requests also in near real time. When a ROI request arrives at the server, a sophisticated progressive image encoding algorithm is performed, but not for the full image. Instead, the encoding algorithm is performed only for the ROI.