Abstract: The present invention relates to method of generating training data for use in animating an animated object corresponding to a deformable object. The method comprises accessing a 3D model of the deformable object, defining a plurality of virtual cameras directed at the 3D model; varying adjustable controls of the 3D model to create a set of deformations on the 3D model. Then, for each deformation, capturing 2D projections of points at each virtual camera, combining the projections to form a vector of 2D point coordinates, generating a vector of 2D shape parameters from the point coordinates, and combining the shape parameters with the values of the adjustable controls for that deformation to form a training data item. The training data items are combined to form a training data set for use in training a learning algorithm for use in animating an animated object corresponding to the deformable object based on real deformations.

Abstract: A method and system for detection and tracking of osteoporosis is disclosed. A method of characterizing an image of a target vertebra includes building a computer model from a set of sample images of pathological and non-pathological variations of vertebrae representing variations in shape of the vertebrae. The method also includes receiving an image of a target vertebra of a subject and automatically estimating contours of lateral outlines of the superior and the inferior cortical endplates of the image. The parameters of the model are varied to determine a set that represents a model shape that approximates the estimated contours of the outlines of the cortical endplates. The method includes automatically characterizing the target vertebra based on the set of model parameters that are determined and outputting on a display device the characterization of the target vertebra.

Abstract: Methods for producing an image indicative of arthritic symptomatology are provided. The methods during a model building phase create a constrained deformable statistical template. The methods then during a runtime phase fit a plurality of loci in a digitized target radiograph of the specified joint; parameterize positions of the plurality of loci fitted in the digitized target radiograph to generate an instance of the statistical template by deriving values for parameters of the digitized target radiograph from the statistical template; search the digitized target radiograph by applying the statistical template to the digitized target radiograph until an optimal fit of the statistical template to at least one region of the digitized target radiograph is found; and produce a comparison image by comparing the at least one region of the digitized target radiograph with the optimal fit of the statistical template.

Abstract: A method and system for characterizing a knee joint in terms of its skeletal morphology. A plurality of loci associated with a model of skeletal structure of a knee joint are fitted and used to parameterize positions of the plurality of loci in a given subject and, thereby, to derive parameters of a deformable statistical template. The skeletal morphology is then characterized on the basis of the derived parameters of the deformable statistical template.

Abstract: A method and system for characterizing a knee joint in terms of its skeletal morphology. A plurality of loci associated with a model of skeletal structure of a knee joint are fitted and used to parameterize positions of the plurality of loci in a given subject and, thereby, to derive parameters of a deformable statistical template. The skeletal morphology is then characterized on the basis of the derived parameters of the deformable statistical template.

Abstract: A method and system for characterizing a knee joint in terms of its skeletal morphology. A plurality of loci associated with a model of skeletal structure of a knee joint are fitted and used to parameterize positions of the plurality of loci in a given subject and, thereby, to derive parameters of a deformable statistical template. The skeletal morphology is then characterized on the basis of the derived parameters of the deformable statistical template.

Abstract: A method and system for detection and tracking of osteoporosis is disclosed. A method of characterizing an image of a target vertebra includes building a computer model from a set of sample images of pathological and non-pathological variations of vertebrae representing variations in shape of the vertebrae. The method also includes receiving an image of a target vertebra of a subject and automatically estimating contours of lateral outlines of the superior and the inferior cortical endplates of the image. The parameters of the model are varied to determine a set that represents a model shape that approximates the estimated contours of the outlines of the cortical endplates. The method includes automatically characterizing the target vertebra based on the set of model parameters that are determined and outputting on a display device the characterization of the target vertebra.

Abstract: A method of generating model data representative of a model in a three-dimensional space of an object from input signals representative of a set of images of the object taken from a plurality of respective camera positions includes the steps of displaying a model image derived from the model data and having a plurality of primitives for viewing by a user, receiving at least one primitive selection signal responsive to user actuation of an input whereby each primitive selection signal identifies a respective selected primitive of the model, and defining a plurality of virtual cameras in the three dimensional space having positions and look directions relative to the model which correspond substantially to those of the respective actual cameras relative to the object.

Abstract: Methods for producing an image indicative of arthritic symptomatology are provided. The methods during a model building phase create a constrained deformable statistical template. The methods then during a runtime phase fit a plurality of loci in a digitized target radiograph of the specified joint; parameterize positions of the plurality of loci fitted in the digitized target radiograph to generate an instance of the statistical template by deriving values for parameters of the digitized target radiograph from the statistical template; search the digitized target radiograph by applying the statistical template to the digitized target radiograph until an optimal fit of the statistical template to at least one region of the digitized target radiograph is found; and produce a comparison image by comparing the at least one region of the digitized target radiograph with the optimal fit of the statistical template.

Abstract: A system and method for cleaning a set of motion capture data, wherein the data correspond to a set of point coordinates relating to a model but may include missing or inaccurate values. A subset of the motion capture data is identified that corresponds to valid points matching locations of corresponding points of the model, and a best set of model parameters is computed in such a manner as to minimize a norm of the valid points with respect to the model. A complete set of point coordinates is then predicted based on the best set of model parameters and a subsequent set of cleaned motion capture data. Actual points are inserted where validated, and the process is iterated until a specified criterion is met.

Abstract: A method and system for characterizing a knee joint in terms of its skeletal morphology. A plurality of loci associated with a model of skeletal structure of a knee joint are fitted and used to parameterize positions of the plurality of loci in a given subject and, thereby, to derive parameters of a deformable statistical template. The skeletal morphology is then characterized on the basis of the derived parameters of the deformable statistical template.

Abstract: A system and method for cleaning a set of motion capture data, wherein the data correspond to a set of point coordinates relating to a model but may include missing or inaccurate values. A subset of the motion capture data is identified that corresponds to valid points matching locations of corresponding points of the model, and a best set of model parameters is computed in such a manner as to minimize a norm of the valid points with respect to the model. A complete set of point coordinates is then predicted based on the best set of model parameters and a subsequent set of cleaned motion capture data. Actual points are inserted where validated, and the process is iterated until a specified criterion is met.

Abstract: A 3-D model of an object is created by processing images taken from a series of camera positions. An initial sequence of the images is processed to define respective image co-ordinates of matching features to generate a set of model data defining model points in a 3-D space of the model and to obtain respective camera solutions representative of positions and orientations of virtual cameras in the 3-D space defining views of the model corresponding to the images. A new image is added to the sequence and processed to obtain a camera solution for a corresponding new virtual camera for use in generating further model data.

Abstract: A 3-D model of an object is created by processing images taken from a series of camera positions. An initial sequence of the images is processed to define respective image co-ordinates of matching features to generate a set of model data defining model points in a 3-D space of the model and to obtain respective camera solutions representative of positions and orientations of virtual cameras in the 3-D space defining views of the model corresponding to the images. A new image is added to the sequence and processed to obtain a camera solution for a corresponding new virtual camera for use in generating further model data.

Abstract: In an apparatus and method for creating a three-dimensional model of an object, images of the object taken from different, unknown positions are processed to identify the points in the images which correspond to the same point on the actual object (that is “matching” points), the matching points are used to determine the relative positions from which the images were taken, and the matching points and calculated positions are used to calculate points in a three-dimensional space representing points on the object. A number of different techniques are used to identify the matching points, and a number of solutions are calculated and tested for the relative positions, the solution which is consistent with the largest number of matching points being selected.

Abstract: In an apparatus and method for creating a three-dimensional model of an object, images of the object taken from different, unknown positions are processed to identify the points in the images which correspond to the same point on the actual object (that is “matching” points), the matching points are used to determine the relative positions from which the images were taken, and the matching points and calculated positions are used to calculate points in a three-dimensional space representing points on the object. A number of different techniques are used to identify the matching points, and a number of solutions are calculated and tested for the relative positions.

Abstract: In an apparatus and method for creating a three-dimensional model of an object, images of the object taken from different, unknown positions are processed to identify the points in the images which correspond to the same point on the actual object (that is “matching” points), the matching points are used to determine the relative positions from which the images were taken, and the matching points and calculated positions are used to calculate points in a three-dimensional space representing points on the object. A number of different techniques are used to identify the matching points, and a number of solutions are calculated and tested for the relative positions, the solution which is consistent with the largest number of matching points being selected.