Abstract: A computer implemented method animates a 3D physical object by first acquiring a 3D graphics model of the object. The model is edited with graphics authoring tools to reflect a desired appearance of the object. The edited model is rendered as an image considering a user location and a location of a virtual light. Then, intensity values of the image are corrected according to an orientation of a surface of the object and a radiance at the surface. The 3D physical object can finally be illuminated with the corrected image to give the 3D physical object the desired appearance under the virtual light when viewed from the user location.

Abstract: A computer implemented method registers an image with a 3D physical object by first acquiring a 3D graphics model of an object. Multiple 3D calibration points a surface of the object and corresponding 3D model calibration points in the 3D graphics model are identified. The object is illuminated with a calibration image using a projector at a fixed location. The calibration image is aligned with each of the 3D calibration points on the surface of the 3D physical object to identify corresponding 2D pixels in the calibration image, and then a transformation between the 2D calibration pixels and the corresponding 3D model calibration points is determined to register the projector with the 3D physical object.

Abstract: This invention integrates model simplification and bounding volume hierarchy construction for collision detection in interactive 3D graphics. In particular, it provides general framework and a preferred method to construct bounding volume hierarchy using outputs of model simplification. Simplified models, besides their application to multi-resolution rendering, can provide clues to the shape of the input object. These clues help in the partitioning of the object's model into components that may be more tightly bounded by simple bounding volumes. The framework and method naturally employ both the bottom-up and the top-down approaches of hierarchy building, and thus can have the advantages of both approaches. The framework and method includes the steps of simplified models generation, component derivation, component tree generation, and bounding volume hierarchy generation.

Abstract: A computer implemented method cross-fades intensities of a plurality of overlapping images by identifying pixels in a target image that are only produced by a first source image. The weights of all the corresponding pixels in the first source image are set to one. Pixels in a second source images contributing to the target image are similarly identified and set to one. the weight of each remaining pixel in the first and second images is inversely proportional to a distance to a nearest pixel having a weight of one. Then, the first and second source image can be projected to form the target image.

Abstract: A computer implemented method cross-fades intensities of a plurality of overlapping images by identifying pixels in a target image that are only produced by a first source image. The weights of all the corresponding pixels in the first source image are set to one. Pixels in a second source images contributing to the target image are similarly identified and set to one. the weight of each remaining pixel in the first and second images is inversely proportional to a distance to a nearest pixel having a weight of one. Then, the first and second source image can be projected to form the target image.

Abstract: A computer implemented method registers an image with a 3D physical object by first acquiring a 3D graphics model of an object. Multiple 3D calibration points a surface of the object and corresponding 3D model calibration points in the 3D graphics model are identified. The object is illuminated with a calibration image using a projector at a fixed location. The calibration image is aligned with each of the 3D calibration points on the surface of the 3D physical object to identify corresponding 2D pixels in the calibration image, and then a transformation between the 2D calibration pixels and the corresponding 3D model calibration points is determined to register the projector with the 3D physical object.

Abstract: A computer implemented method animates a 3D physical object by first acquiring a 3D graphics model of the object. The model is edited with graphics authoring tools to reflect a desired appearance of the object. The edited model is rendered as an image considering a user location and a location of a virtual light. Then, intensity values of the image are corrected according to an orientation of a surface of the object and a radiance at the surface. The 3D physical object can finally be illuminated with the corrected image to give the 3D physical object the desired appearance under the virtual light when viewed from the user location.