Abstract: Modeling cross-sections of yarn may include receiving yarn simulation input comprising a descriptive model of a general curvature followed by the yarn, providing a plurality of fibers distributed radially from the center of a ply, setting a base position based on parameters, applying a strain model to simulate the effect of stretch forces applied to the yarn, and outputting a yarn model indicating position and directionality of fibers in the yarn. The technology also relates to real-time modeling of a garment comprising a fabric. For instance, real-time modeling of a garment may include providing an input associated with one or more parameters of the fabric, receiving frames of a computer simulated garment, the computer simulated garment including a simulation of the fabric, the fabric simulation including yarns simulated based on a yarn model.

Abstract: A learning-based clothing animation method and system for highly efficient virtual try-on simulations is provided. Given a garment, the system preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using a database, the system trains a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. A model according to embodiments separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. A recurrent neural network is provided to regress garment wrinkles, and the system achieves highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods.

Abstract: A learning-based clothing animation method and system for highly efficient virtual try-on simulations is provided. Given a garment, the system preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using a database, the system trains a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. A model according to embodiments separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. A recurrent neural network is provided to regress garment wrinkles, and the system achieves highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods.

Abstract: A learning-based clothing animation method and system for highly efficient virtual try-on simulations is provided. Given a garment, the system preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using a database, the system trains a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. A model according to embodiments separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. A recurrent neural network is provided to regress garment wrinkles, and the system achieves highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods.

Abstract: The technology relates to modeling cross-sections of yarn. For instance, modeling cross-sections of yarn may include receiving yarn simulation input comprising a descriptive model of a general curvature followed by the yarn, providing a plurality of fibers distributed raidally from the center of a ply, setting a base position based on parameters, applying a strain model to simulate the effect of stretch forces applied to the yarn, and outputting a yarn model indicating position and directionality of fibers in the yarn. The technology also relates to real-time modeling of a garment comprising a fabric. For instance, real-time modeling of a garment may include providing an input associated with one or more parameters of the fabric, receiving frames of a computer simulated garment, the computer simulated garment including a simulation of the fabric, the fabric simulation including yarns simulated based on a yarn model.

Abstract: A learning-based clothing animation method and system for highly efficient virtual try-on simulations is provided. Given a garment, the system preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and animations. Then, using a database, the system trains a learning-based model of cloth drape and wrinkles, as a function of body shape and dynamics. A model according to embodiments separates global garment fit, due to body shape, from local garment wrinkles, due to both pose dynamics and body shape. A recurrent neural network is provided to regress garment wrinkles, and the system achieves highly plausible nonlinear effects, in contrast to the blending artifacts suffered by previous methods.

Abstract: In an object generation system, consumable base materials are characterized in a characterization process wherein an object generation system can use a plurality of so-characterized base materials. User input representing a desired object and set of characteristics for that desired object are processed, using a computer or computing device, to derive a mapping of locations for placement of portions of the plurality of base materials such that when the mapping is provided to an object generator, the generated object approximates the representing a desired object and set of characteristics. The characterization of a base material might include elasticity of the base material, the user input might be a desired shape and elasticity, the object generator might be a 3D multi-material printer and the generated object might at least approximate the desired shape and elasticity as a result of being constructed from the plurality of base materials used by the printer.

Abstract: In an object generation system, consumable base materials are characterized in a characterization process wherein an object generation system can use a plurality of so-characterized base materials. User input representing a desired object and set of characteristics for that desired object are processed, using a computer or computing device, to derive a mapping of locations for placement of portions of the plurality of base materials such that when the mapping is provided to an object generator, the generated object approximates the representing a desired object and set of characteristics. The characterization of a base material might include elasticity of the base material, the user input might be a desired shape and elasticity, the object generator might be a 3D multi-material printer and the generated object might at least approximate the desired shape and elasticity as a result of being constructed from the plurality of base materials used by the printer.

Abstract: In an object generation system, consumable base materials are characterized in a characterization process wherein an object generation system can use a plurality of so-characterized base materials. User input representing a desired object and set of characteristics for that desired object are processed, using a computer or computing device, to derive a mapping of locations for placement of portions of the plurality of base materials such that when the mapping is provided to an object generator, the generated object approximates the representing a desired object and set of characteristics. The characterization of a base material might include elasticity of the base material, the user input might be a desired shape and elasticity, the object generator might be a 3D multi-material printer and the generated object might at least approximate the desired shape and elasticity as a result of being constructed from the plurality of base materials used by the printer.

Abstract: In an object generation system, consumable base materials are characterized in a characterization process wherein an object generation system can use a plurality of so-characterized base materials. User input representing a desired object and set of characteristics for that desired object are processed, using a computer or computing device, to derive a mapping of locations for placement of portions of the plurality of base materials such that when the mapping is provided to an object generator, the generated object approximates the representing a desired object and set of characteristics. The characterization of a base material might include elasticity of the base material, the user input might be a desired shape and elasticity, the object generator might be a 3D multi-material printer and the generated object might at least approximate the desired shape and elasticity as a result of being constructed from the plurality of base materials used by the printer.

Abstract: An apparatus comprises a manipulandum, a housing, a sensor and an actuator. The housing has a palpation region spaced apart from the manipulandum. The sensor is coupled to the palpation region of the housing. The sensor is configured to send a signal based on a palpation of the palpation region of the housing. The actuator is coupled to the manipulandum. The actuator is configured to send haptic output to the manipulandum based on the signal.

Abstract: An apparatus comprises a manipulandum, a housing, a sensor and an actuator. The housing has a palpation region spaced apart from the manipulandum. The sensor is coupled to the palpation region of the housing. The sensor is configured to send a signal based on a palpation of the palpation region of the housing. The actuator is coupled to the manipulandum. The actuator is configured to send haptic output to the manipulandum based on the signal.