Amazon Technologies, Inc.

Brandon Michael Smith

Amit Kumar Agrawal

Prakash Ramu

Jinjin Li

Visesh Uday Kumar Chari

Sunil Sharadchandra Hadap

Apoorv Chaudhri

Ram Sever

Durga Venkata Kiran Yakkala

Antonio Criminisi

Rohith Mysore Vijaya Kumar

Rajesh Gautam

Dylan John Drover

Noam Sorek

Siddharth Choudhary

Geoffrey L Larson

David D Wilson

Ridge Carpenter

Ganesh Subramanian Iyer

Curtis Holmes

Described are systems and method directed to generation of a dimensionally accurate three-dimensional ('3D') model of a body, such as a human body, based on two-dimensional (“2D”) images of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of their body from different views with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model or avatar of the body of the user.

Three-dimensional body model from a two-dimensional body image

Described are systems and methods directed to a body change journey that utilizes one or more current body measurement values, one or more goal body measurement values, and a cohort to determine a body change journey that a user can follow to progress from the current body measurement value to the goal body measurement value. The cohort may include a plurality of data of other bodies who have progressed from a starting body measurement value that is similar to the current body measurement value.

Cohort based body change journeys

Described are systems and methods to determine one or more body dimensions of a body based on a processing of one or more two-dimensional images that include a representation of the body. Body dimensions include any length, circumference, etc., of any part of a body, such as shoulder circumference, chest circumference, waist circumference, hip circumference, inseam length, bicep circumference, leg circumference, etc.

Body dimensions from two-dimensional body images

Described are systems and methods directed to generation of a dimensionally accurate three-dimensional ('3D') model of a body, such as a human body, based on two-dimensional (“2D”) images of at least a portion of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of at least a portion of their body from different views with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model or avatar of the body of the user.

Three-dimensional body composition from two-dimensional images of a portion of a body

Described are systems and methods directed to generation of a personalized three-dimensional ('3D') body model of a body, such as a human body, based on two-dimensional ('2D') images of that body and the generation and presentation of predicted personalized 3D body models of the body when one or more body measurements (e.g., body fat, body weight, muscle mass) are changed. For example, a user may provide a target body measurement value and the implementations will generate one or more predicted personalized 3D body models representative of a predicted appearance of the body with the target body measurement value.

Generation and presentation of predicted personalized three-dimensional body models

Described are systems and method directed to generation of a dimensionally accurate three-dimensional ('3D') model of a body, such as a human body, based on two-dimensional ('2D') images of that body. A user may use a 2D camera, such as a digital camera typically included in many of today's portable devices (e.g., cell phones, tablets, laptops, etc.) and obtain a series of 2D body images of their body from different views with respect to the camera. The 2D body images may then be used to generate a plurality of predicted body parameters corresponding to the body represented in the 2D body images. Those predicted body parameters may then be further processed to generate a dimensionally accurate 3D model or avatar of the body of the user.

Three-dimensional body composition from two-dimensional images

Predictive personalized three-dimensional body models

Growing community of inventors

Fremont, CA, United States of America

Brandon Michael Smith