Abstract:
A system and method for constructing a 3D scene model comprising 3D objects and representing a scene, based upon a prior 3D scene model. The method comprises the steps of acquiring an image of the scene; initializing the computed 3D scene model to the prior 3D scene model; and modifying the computed 3D scene model to be consistent with the image. The step of modifying the computed 3D scene models consists of the sub- steps of comparing data of the image with objects of the 3D scene model, resulting in associated data and unassociated data; using the unassociated data to compute new objects that are not in the 3D scene model and adding the new objects to the 3D scene model; and using the associated data to detect objects in the prior 3D scene model that are absent and removing the absent objects from the 3D scene model. The present invention may also be used to construct multiple alternative 3D scene models.
Abstract:
A system and method for acquiring three-dimensional (3-D) images of a scene. The system includes a projection device for projecting a locally unique pattern (LUP) onto a scene, and sensors for imaging the scene containing the LUP at two or more viewpoints. A computing device matches corresponding pixels in the images by using the local uniqueness of the pattern to produce a disparity map. A range map can then be generated by triangulating points in the imaged scene.
Abstract:
A method for rapidly determining feasibility of a force optimization problem and for rapidly solving a feasible force optimization problem is disclosed. The method comprises formulating the force optimization problem or force feasibility problem as a convex optimization problem, formulating a primal barrier subproblem associated with the convex optimization problem, and solving the primal barrier subproblem. The method and related methods may also be used to solve each problem in a set of force optimization problems, determine the minimum or maximum force required to satisfy any of a set of force optimization problems, solve a force closure problem, compute a conservative contact force vector, or solve a feasible force optimization problem with bidirectional forces.
Abstract:
A method for rapidly determining feasibility of a force optimization problem and for rapidly solving a feasible force optimization problem is disclosed. The method comprises formulating the force optimization problem or force feasibility problem as a convex optimization problem, formulating a primal barrier subproblem associated with the convex optimization problem, and solving the primal barrier subproblem. The method and related methods may also be used to solve each problem in a set of force optimization problems, determine the minimum or maximum force required to satisfy any of a set of force optimization problems, solve a force closure problem, compute a conservative contact force vector, or solve a feasible force optimization problem with bidirectional forces.
Abstract:
A system and method for acquiring three-dimensional (3-D) images of a scene. The system includes a projection device (P1)for projecting a locally unique pattern (LUP) onto a scene, and sensors (C1, C2, C3) for imaging the scene containing the LUP at two or more viewpoints. A computing device matches corresponding pixels in the images by using the local uniqueness of the pattern to produce a disparity map. A range map can then be generated by triangulating points in the imaged scene.