Abstract: A technique for solving an inverse-kinematic problem by interpolating solutions from examples. Example poses or motions of an object are collected and annotated. The annotations are essentially parameters for a function—i.e., the function X(p) generates degree-of-freedom values of an object that is posed in a manner that satisfies parameters p. The analytic function X is interpolated from these examples and improved automatically based on kinematic measurements. Preferably, the interpolation is created by taking a weighted sum of cardinal basis functions having linear and radial parts, Preferably, the interpolation is a weighted sum of cardinal basis functions having linear and radial portions.

Abstract: A spectator experience corresponding to an occurrence of one or more games or events is generated based on each associated occurrence. The occurrence of a game or event varies in response to contributions and/or interactions of one or more participants of the game or event. The spectator experience enables users thereof to observe an augmented version of the game or event, such as by implementing enhanced viewpoint controls and/or other spectator related effects. In a particular aspect, the spectator experience can provide an indication of the spectators' presence, which is made available to the spectators and/or to the participants of the game.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: A technique for solving an inverse-kinematic problem by interpolating solutions from examples. Example poses or motions of an object are collected and annotated. The annotations are essentially parameters for a function—i.e., the function X(p) generates degree-of-freedom values of an object that is posed in a manner that satisfies parameters p. The analytic function X is interpolated from these examples and improved automatically based on kinematic measurements. Preferably, the interpolation is created by taking a weighted sum of cardinal basis functions having linear and radial parts. Preferably, the interpolation is a weighted sum of cardinal basis functions having linear and radial portions.

Abstract: A technique for solving an inverse-kinematic problem by interpolating solutions from examples. Example poses or motions of an object are collected and annotated. The annotations are essentially parameters for a function—i.e., the function X(p) generates degree-of-freedom values of an object that is posed in a manner that satisfies parameters p. The analytic function X is interpolated from these examples and improved automatically based on kinematic measurements. Preferably, the interpolation is created by taking a weighted sum of cardinal basis functions having linear and radial parts, Preferably, the interpolation is a weighted sum of cardinal basis functions having linear and radial portions.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: A technique for solving an inverse-kinematic problem by interpolating solutions from examples. Example poses or motions of an object are collected and annotated. The annotations are essentially parameters for a function—i.e., the function x(p) generates degree-of-freedom values of an object that is posed in a manner that satisfies parameters p. The analytic function X is interpolated from these examples and improved automatically based on kinematic measurements. Preferably, the interpolation is created by taking a weighted sum of cardinal basis functions having linear and radial parts, Preferably, the interpolation is a weighted sum of cardinal basis functions having linear and radial portions.

Abstract: A spectator experience corresponding to an occurrence of one or more games or events is generated based on each associated occurrence. The occurrence of a game or event varies in response to contributions and/or interactions of one or more participants of the game or event. The spectator experience enables users thereof to observe an augmented version of the game or event, such as by implementing enhanced viewpoint controls and/or other spectator related effects. In a particular aspect, the spectator experience can provide an indication of the spectators' presence, which is made available to the spectators and/or to the participants of the game.

Abstract: Shadows, which play an important role in perceiving the shape and texture of an object, are simulated interactively in a real time, self-shadowing of a bump mapped surface for a computer rendered object. A computer graphics textured object function defines a horizon map over an orientation in a tangent space of the object using different textures or basis functions. The implementation can be performed using commodity graphics hardware by precomputing the horizon map for limited visibility for each point on the bump mapped surface given light in each of a plurality of radial directions. The horizon map is used to produce self-shadowing of the bump mapped surface of the object.

Abstract: A method and computer product for rendering real-time three-dimensional images on a display based on view manipulation of prestored depth images in a global coordinate space. First, a layered depth image is generated from multiple depth images based on a predetermined display viewpoint. If the determined viewpoint is within a predetermined threshold of the layered depth image, the generated layered depth image is warped based on the determined display viewpoint, pixels from the layered depth image are splatted onto the warped image, and an output image is generated and displayed based on the splat pixels. If the determined viewpoint is outside the predetermined threshold of the previously generated layered depth image, a next closest layered depth image is generated. If the next closest layered depth image is not fully generated, the previously generated layered depth image is used to generate an output image.

Abstract: A system for providing improved computer animation can be used in interactive applications such as 3D video games and virtual environments. Tie system comprises an offline authoring system with tools for constructing controllable “verbs” from sets of motion example segments, and for constructing transitions between different verbs; and a runtime system for controlling the invocation of the verbs as parameterized by user defined “adverbs”. The system involves interpolating predefined animation segments created by an animator or through motion capture video. The animation segments are made up of data representing selected points on the animated creature (e.g., the joints and extremities) and values, as a function of time, for each degree of freedom of those points. In addition, a “verb graph” is constructed to act as the glue to assemble verbs and their adverbs into a runtime data structure. The verb graph defines the allowable transitions from one verb to another verb.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: A method is presented comprising rendering a virtual character to interface with at least a user, and controlling one or more anatomical attributes of the virtual character based, at least in part, on a scientifically-based model of physically expressive behavior for that anatomical attribute.

Abstract: A computer-based method and system for digital 3-dimensional imaging of an object which allows for viewing images of the object from arbitrary vantage points. The system, referred to as the Lumigraph system, collects a complete appearance of either a synthetic or real object (or a scene), stores a representation of the appearance, and uses the representation to render images of the object from any vantage point. The appearance of an object is a collection of light rays that emanate from the object in all directions. The system stores the representation of the appearance as a set of coefficients of a 4-dimensional function, referred to as the Lumigraph function. From the Lumigraph function with these coefficients, the Lumigraph system can generate 2-dimensional images of the object from any vantage point. The Lumigraph system generates an image by evaluating the Lumigraph function to identify the intensity values of light rays that would emanate from the object to form the image.