Abstract:
A method recovers a 3D model of non-rigid 3D shape and motion of an object directly from an input video of the object by first identifying a set of features on the object in a reference image of the input video. Correspondences are then determined between the set of features in the reference image and corresponding features in each other image of the input video, These correspondences are factored by cascaded singular value decompositions into a motion matrix and a shape matrix. The 3D model can then be extracted from the factored motion matrix and shape matrix. The 3D model includes a linear basis for deformable shape of the object in the input video, and for each image a 3D rotations matrix, deformation coefficients, and translation vectors. A novel video can now be generated from the input video by manipulating the 3D model.
Abstract:
Keystrokes on a keyboard are predicted by constructing a model from a training corpus. The training corpus includes symbol sequences. The model predicts a set of symbols, where each symbol of the set continues a particular symbol sequence using variable-length subsequences of the particular symbol sequence. A particular length is chosen to maximize a probability that the predicting is correct. Keys on the keyboard are highlighted. The highlighted keys correspond to selected symbols in the set of symbols.
Abstract:
A method performs an image processing application by expressing the image processing application as a non-negative quadratic program (NNQP) with a quadratic objective, and nonnegativity constraints. A Karush-Kuhn-Tucker condition of the NNQP is expressed as a fixpoint ratio. Then, the fixpoint ratio is determined iteratively until a solution to the image processing application is reached with a desired precision.
Abstract:
Radiation doses are optimized by providing a model of the set of beams and a target dose in normalized forms. A Gram matrix is determined from the model. The target dose is subsampled to determine initial intensity values for the set of beams. Then, the following steps are iterated until convergence. A very small positive value, 0
Abstract:
A motion of a first car and a second car in a multi-car elevator system, wherein the first car and the second car move independently in an elevator shaft, is controlled by generating a command to move the first car according to a first deceleration curve, if a relationship between a position and a velocity of the first car corresponds to a value on the first deceleration curve; and by generating a command to move the second car according to a second deceleration curve, if a relationship between position and a velocity of the second car corresponds to a value on the second deceleration curve, wherein a distance between the first and the second deceleration curve is equals or greater than a minimum distance.
Abstract:
A method for controlling a motion of a first car and a second car in a multi-car elevator system, wherein the first car and the second car move independently in an elevator shaft, determines alternately motion plans for the first the second cars wherein each part of a motion plan for the first car is determined for a planning period of the first car, wherein a beginning of the planning period of the first car is determined by an end of the planning period of the second car, and an end of the planning period of the first car is determined by a home position of the first car on the motion plan, wherein the part of the motion plan is determined based on motion constraints, a set of requests, and the motion plan of the second car determined by the beginning of the planning period of the first car.
Abstract:
A method performs an image processing application by expressing the image processing application as a non-negative quadratic program (NNQP) with a quadratic objective, and nonnegativity constraints. A Karush-Kuhn-Tucker condition of the NNQP is expressed as a fixpoint ratio. Then, the fixpoint ratio is determined iteratively until a solution to the image processing application is reached with a desired precision.
Abstract:
A method edits editing an input image to produce an output image by first partitioning pixels of the input image into sets of adjacent pixels. Then, for each set, a trellis of nodes connected by directed links is defined. Each node corresponds to one of the pixels in the set of pixels, and an action and location of the pixel in the output image. Costs are assigned to the nodes and the links. A least cost path through the trellis is determined, and pixels corresponding to the nodes on the least cost path are edited according to the action and location to form the output image.
Abstract:
A method for controlling a motion of a first car and a second car in a multi-car elevator system, wherein the first car and the second car move independently in an elevator shaft, determines alternately motion plans for the first the second cars wherein each part of a motion plan for the first car is determined for a planning period of the first car, wherein a beginning of the planning period of the first car is determined by an end of the planning period of the second car, and an end of the planning period of the first car is determined by a home position of the first car on the motion plan, wherein the part of the motion plan is determined based on motion constraints, a set of requests, and the motion plan of the second car determined by the beginning of the planning period of the first car.