In various example embodiments, devices, systems, and methods for a waist measuring belt are provided. An example waist measuring belt is made up of a belt buckle frame with attachments for a belt strap. The belt further includes a position measuring module coupled to the belt buckle frame that measures an attachment position of a second end of the belt strap to the belt buckle frame. The belt also includes a tension measuring module coupled to the belt buckle frame that measures a tension through the belt buckle frame and the belt strap. A memory and a wireless communication module attached to the belt may be used to store measurements and communicate with a mobile device or server. In various embodiments, estimated user waist sizes over time using measured values and belt-specific data may be used to estimate a user's waist size and generate a waist size history.

The disclosure provides a measurement garment and a measuring system. The measurement garment includes a first recognition pattern. The first recognition pattern is disposed at a stretchable part of the measurement garment, wherein the first recognition pattern comprises a first reference point and a second reference point, the stretchable part corresponds to a body part of a wearer wearing the measurement garment, and a specific distance between the first reference and a second reference point varies in response to the body part, and a variation of the specific distance is used for measuring a dimension of the body part.

The disclosure herein relates to the fashion and styling industry. In particular, aspects of the disclosure relates to technologies and methods for generating automatic garment-based and outfit-based styling recommendations based upon selected physical body characteristics and garment characteristics that are most critical for good styling. The disclosure provides simplified rule-based styling logic. The rule based logic is using a small set of physical body characteristics referred to as styling anchors to be matched with a garment molds. The matching for a good styling is based upon applying a combination of associated rules of a garment mold specified as a major class definition of a garment type (skirts, pants, tops, jackets, dresses) with a sub-class definition (neckline shape, waistline position, sleeves, length) to provide a do-able and simplified process of personal styling recommendation.

The disclosure herein relates to the fashion and styling industry. In particular, aspects of the disclosure relates to technologies and methods for generating automatic garment-based and outfit-based styling recommendations based upon selected physical body characteristics and garment characteristics that are most critical for good styling. The disclosure provides simplified rule-based styling logic. The rule based logic is using a small set of physical body characteristics referred to as styling anchors to be matched with a garment molds. The matching for a good styling is based upon applying a combination of associated rules of a garment mold specified as a major class definition of a garment type (skirts, pants, tops, jackets, dresses) with a sub-class definition (neckline shape, waistline position, sleeves, length) to provide a do-able and simplified process of personal styling recommendation.

A series of captured images of a user is received. Using a processor, the images are processed to identify a portion of each of the images corresponding to the user. Parameters of a predetermined three-dimensional human model are modified to fit a modified version of the predetermined three-dimensional human model across the identified portions of the images to determine a set of specific parameters representing a body profile of the user.

A series of captured images of a user is received. Using a processor, the images are processed to identify a portion of each of the images corresponding to the user. Parameters of a predetermined three-dimensional human model are modified to fit a modified version of the predetermined three-dimensional human model across the identified portions of the images to determine a set of specific parameters representing a body profile of the user.

A system comprising a machine-readable storage medium storing at least one program and a computer-implemented method for collecting body measurements of a human user using a body measurement garment is provided. The body measurement garment comprises a plurality of sensors configured to produce a set of output data. The method may include receiving the set of output data from the body measurement garment and determining a plurality of body measurements from the output data. The method may further include generating a body shape model representing the shape of the body of the user. The method may also include generating a garment fit model representing the fit of a garment on the human user.

A system comprising a machine-readable storage medium storing at least one program and a computer-implemented method for collecting body measurements of a human user using a body measurement garment is provided. The body measurement garment comprises a plurality of sensors configured to produce a set of output data. The method may include receiving the set of output data from the body measurement garment and determining a plurality of body measurements from the output data. The method may further include generating a body shape model representing the shape of the body of the user. The method may also include generating a garment fit model representing the fit of a garment on the human user.

Systems and methods for automatically determining of garment sizing (e.g., fit) using a images including video images. The method may perform non-contact estimations of garment fit from visual (e.g., video) input by receiving an video of the subject's head and face and profile and determining a scaling factor from the subject's intraocular spacing and using this scaling factor when analyzing images of other body regions to determine garment sizing.

Systems and methods for automatically determining of garment sizing (e.g., fit) using a images including video images. The method may perform non-contact estimations of garment fit from visual (e.g., video) input by receiving an video of the subject's head and face and profile and determining a scaling factor from the subject's intraocular spacing and using this scaling factor when analyzing images of other body regions to determine garment sizing.