A system for recommending a size of a wearable item implements a method that includes identifying a reference wearable item and a size for the reference wearable item. The system accesses a wearable item database and retrieves a three-dimensional model of the reference wearable item. The system also receives, via a user interface, a functional requirement. The system accesses the wearable item database and identifies set of candidate objects, each of which satisfies the functional requirement. Based on the size of the reference wearable item, the system will determine a size for each of the candidate objects. The system will select at least one of the plurality of candidate objects as a recommended object and presents each recommended object and the size of each recommended object to a user.

A system for recommending a size of a wearable item implements a method that includes identifying a reference wearable item and a size for the reference wearable item. The system accesses a wearable item database and retrieves a three-dimensional model of the reference wearable item. The system also receives, via a user interface, a functional requirement. The system accesses the wearable item database and identifies set of candidate objects, each of which satisfies the functional requirement. Based on the size of the reference wearable item, the system will determine a size for each of the candidate objects. The system will select at least one of the plurality of candidate objects as a recommended object and presents each recommended object and the size of each recommended object to a user.

Techniques for extraction of body parameters, dimensions and shape of a customer are presented herein. A model descriptive of a garment, a corresponding calibration factor and reference garment shapes can be assessed. A garment shape corresponding to the three-dimensional model can be selected from the reference garment shapes based on a comparison of the three-dimensional model with the reference garment shapes. A reference feature from the plurality of reference features may be associated with the model feature. A measurement of the reference feature may be calculated based on the association and the calibration factor. The computed measurement can be stored in a body profile associated with a user. An avatar can be generated for the user based on the body profile and be used to show or indicate fit of a garment, as well as make fit and size recommendations.

Techniques for extraction of body parameters, dimensions and shape of a customer are presented herein. A model descriptive of a garment, a corresponding calibration factor and reference garment shapes can be assessed. A garment shape corresponding to the three-dimensional model can be selected from the reference garment shapes based on a comparison of the three-dimensional model with the reference garment shapes. A reference feature from the plurality of reference features may be associated with the model feature. A measurement of the reference feature may be calculated based on the association and the calibration factor. The computed measurement can be stored in a body profile associated with a user. An avatar can be generated for the user based on the body profile and be used to show or indicate fit of a garment, as well as make fit and size recommendations.

The present invention relates to a bra fitting method for determining and presenting customized advice for bras. Compared to existing methods the present method is based on an optimized fitting of the bodily dimensions with the functional characteristics of a bra model. Applying a given technique, the present invention incorporates the functional characteristics, and in particular the lifting, shaping and covering of the bra in the brassiere measurement method. As such the method of the present invention results in a customized advice, allowing users to gain insights in the fitting requirements and providing them with a confidence to seek and identify a correctly fitting bra.

The present invention relates to a bra fitting method for determining and presenting customized advice for bras. Compared to existing methods the present method is based on an optimized fitting of the bodily dimensions with the functional characteristics of a bra model. Applying a given technique, the present invention incorporates the functional characteristics, and in particular the lifting, shaping and covering of the bra in the brassiere measurement method. As such the method of the present invention results in a customized advice, allowing users to gain insights in the fitting requirements and providing them with a confidence to seek and identify a correctly fitting bra.

Embodiments of the present invention provide a method, system and computer program product for computer assisted pattern drafting in garment development. In an embodiment of the invention, a pattern making method includes initially acquiring a multiplicity of different two-dimensional image slices of a human form. Thereafter, a panel of a portion of a pattern of a garment is selected for processing in a data processing system and a metric computational rule for the selected panel is mapped to one of the two-dimensional image slices. A measurement of the one of the two-dimensional image slices is then acquired and the mapped metric computational rule is applied using the acquired measurement to produce a measurement for the selected panel.

Techniques for three-dimensional garment simulation using parallel computing are presented herein. An access module can be configured to access a three-dimensional garment model of a garment. The garment model can include garment points that represent a surface of the garment. A processor, having a plurality of cores, can be configured by a garment simulation module to calculate one or more exerted forces on a subset of garment points. Additionally, the garment simulation module can generate cross pairs and apportion the generated cross pairs among the plurality of cores. Moreover, the garment simulation module can determine, using the plurality of vector execution units in parallel based on an organized data layout, whether boundaries of the first subgroup of cross pairs are overlapping based on the one or more exerted forces. Subsequently, the garment simulation module can calculate one or more simulated forces acting on the garment points based on the determination.

Techniques for three-dimensional garment simulation using parallel computing are presented herein. An access module can be configured to access a three-dimensional garment model of a garment. The garment model can include garment points that represent a surface of the garment. A processor, having a plurality of cores, can be configured by a garment simulation module to calculate one or more exerted forces on a subset of garment points. Additionally, the garment simulation module can generate cross pairs and apportion the generated cross pairs among the plurality of cores. Moreover, the garment simulation module can determine, using the plurality of vector execution units in parallel based on an organized data layout, whether boundaries of the first subgroup of cross pairs are overlapping based on the one or more exerted forces. Subsequently, the garment simulation module can calculate one or more simulated forces acting on the garment points based on the determination.

Disclosed are methods and systems for generating a customized garment design. The method, when executed by a processor, comprises first receiving user data, generating at least one user signal, identifying a preferred garment category by analyzing the user data, retrieving related third-party data and public data, and retrieving features for the identified garment category from a database. For features associated with cuts and fabrics, preferred cut values and preferred fabric values are identified based on previously received data, and corresponding value scores computed. For other features, preferred feature values are identified, and corresponding value scores computed. One or more feature sets are generated by selecting a preferred value for each feature, where an associated feature set score is computed based on the value scores and one or more score adjustments. A customized garment design is generated by selecting a feature set with a high feature set score.