Abstract: In one embodiment of the invention, a method for a robotic system is disclosed to track one or more robotic instruments. The method includes generating kinematics information for the robotic instrument within a field of view of a camera; capturing image information in the field of view of the camera; and adaptively fusing the kinematics information and the image information together to determine pose information of the robotic instrument. Additionally disclosed is a robotic medical system with a tool tracking sub-system. The tool tracking sub-system receives raw kinematics information and video image information of the robotic instrument to generate corrected kinematics information for the robotic instrument by adaptively fusing the raw kinematics information and the video image information together.

Abstract: In one embodiment of the invention, a method is disclosed to locate a robotic instrument in the field of view of a camera. The method includes capturing sequential images in a field of view of a camera. The sequential images are correlated between successive views. The method further includes receiving a kinematic datum to provide an approximate location of the robotic instrument and then analyzing the sequential images in response to the approximate location of the robotic instrument. An additional method for robotic systems is disclosed. Further disclosed is a method for indicating tool entrance into the field of view of a camera.

Abstract: A scene-based non-uniformity correction method employing local constant statistics for eliminating fixed pattern noise in a video comprising a plurality of images is disclosed, comprising the steps of providing an initial gain image, an initial offset image, a predetermined pyramid level, and a filter of a predetermined level; setting one of the plurality of input images to the current image; calculating a temporary true scene image for the current image based on the initial gain image and the initial offset image; accumulating a temporal mean image and a temporal standard deviation image based on the calculated temporary true scene image; setting another of the plurality of images to the current image and repeating the setting, calculating, and accumulating steps until substantially all of the images of the plurality of images have been processed, otherwise further perform the steps of calculating a Gaussian mean image based on the accumulated temporal mean and calculating a Gaussian gain image based on the

Abstract: A scene based non-uniformity, correction method super-resolution for eliminating fixed pattern noise in a video having a plurality of input images is disclosed, comprising, the steps of warping, each of the plurality of images with respect to a reference image to obtain a warped set of images; performing one of averaging and deblurring on the warped set of images to obtain an initial estimate of a reference true scene flame; warping the initial estimate of the reference true scene frame with respect to each of the plurality of images to obtain a set of estimated true signal images; performing a least square fit algorithm to estimate a gain image and an offset image given the set of estimated true signal images; applying the estimated gain image and estimated offset image to the plurality of images to obtain a clean set of images; and applying a super-resolution algorithm to the clean set of images to obtain a higher resolution version of the reference true scene frame.

Abstract: A method and apparatus for performing two-dimensional video alignment onto three-dimensional point clouds. The system recovers camera pose from camera video, determines a depth map, converts the depth map to a Euclidean video point cloud, and registers two-dimensional video to the three-dimensional point clouds.

Abstract: A method and apparatus for performing two-dimensional video alignment onto three-dimensional point clouds. The system recovers camera pose from camera video, determines a depth map, converts the depth map to a Euclidean video point cloud, and registers two-dimensional video to the three-dimensional point clouds.

Abstract: A method and apparatus for performing iris recognition from at least one image is disclosed. A plurality of cameras is used to capture a plurality of images where at least one of the images contains a region having at least a portion of an iris. At least one of the plurality of images is then processed to perform iris recognition.

Abstract: A method and apparatus for performing georegistration using both a telemetry based rendering technique and an interative rendering technique. The method begins with a telemetry based rendering that produces reference imagery that substantially matches a view being imaged by the camera. The reference imagery is rendered using the telemetry of the present camera orientation. Upon obtaining a certain level of accuracy, the method proceeds to perform iterative rendering. During iterative rendering, the method uses image motion information from the video to enhance rendering of the reference imagery. A further embodiment uses sequential statistical framework to provide a unified approach to georegistration.

Abstract: A method and apparatus for determining the optical flow of a sequence of image frames. Optical flow fields are computed in a manner that enforces both brightness constancy and a consistency constraint.

Abstract: A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e.g., dynamically generated video images, and thus achieve a high accuracy identification of locations within the scene. When a sensor, such as a video camera, images a scene contained in the geo-spatial database, the system recalls a reference image pertaining to the imaged scene. This reference image is aligned very accurately with the sensor's images using a parametric transformation. Thereafter, other information that is associated with the reference image can easily be overlaid upon or otherwise associated with the sensor imagery.

Abstract: A system and method for accurately mapping between image coordinates and geo-coordinates, called geo-spatial registration. The system utilizes the imagery and terrain information contained in the geo-spatial database to precisely align geodetically calibrated reference imagery with an input image, e.g., dynamically generated video images, and thus achieve a high accuracy identification of locations within the scene. When a sensor, such as a video camera, images a scene contained in the geo-spatial database, the system recalls a reference image pertaining to the imaged scene. This reference image is aligned very accurately with the sensor's images using a parametric transformation. Thereafter, other information that is associated with the reference image can easily be overlaid upon or otherwise associated with the sensor imagery.