System, method, and apparatus for generating a three-dimensional representation from one or more two-dimensional images
In a system and method for generating a 3-dimensional representation of a portion of an organism, collecting training data, wherein the training data includes a first set of training data and a second set of training data. At least one statistical model having a set of parameters is built using the training data. The at least one statistical model is compared to a 2-dimensional image of the portion of the organism. At least one parameter of the set of parameters of the statistical model is modified based on the comparison of the at least one statistical model to the 2-dimensional image of the portion of the organism. The modified set of parameters representing the portion of the organism is passed through the statistical model.
1. A method for generating a 3-dimensional representation of a portion of an organism using a processor, comprising:
collecting training data and storing the training data in a database, wherein the training data includes a first set of training data and a second set of training data, and wherein each of the first set of training data and the second set of training data comprises a plurality of points representing the organism;
building at least one statistical model having a set of parameters using the training data;
comparing the at least one statistical model to a 2-dimensional image of the portion of the organism using the processor;
modifying at least one parameter of the set of parameters of the statistical model based on the comparison of the at least one statistical model to the 2-dimensional image of the portion of the organism; and
passing the modified set of parameters representing the portion of the organism through the statistical model.
2. The method according to claim 1 , wherein the training data includes data relating to portions of organisms of the same type as the portion of the organism.
3. The method according to claim 1 , wherein the statistical model is based on at least one of 2-dimensional shape, 2-dimensional texture, 3-dimensional shape and 3-dimensional texture.
4. The method according to claim 3 , wherein the 2-dimensional shape is based on a first plurality of points representing the first set of training data and a second plurality of points representing the second set of training data.
5. The method according to claim 3 , wherein the 2-dimensional texture is based on pixel values inside the 2-dimensional shape.
6. The method according to claim 5 , wherein the pixel values represent the colors red, green and blue.
7. The method according to claim 3 , wherein the 3-dimensional shape is based on a first plurality of points, a second plurality of points, a third plurality of points and a fourth plurality of points obtained from at least one of a 3-dimensional acquisition system and 2-dimensional images.
8. The method according to claim 3 , wherein the 3-dimensional texture is based on pixel values located between 3-dimensional points.
9. A method for generating a 3-dimensional representation of a portion of an object that is capable of being represented by a statistical model using a processor, comprising:
collecting training data and storing the training data in a database, wherein the training data includes a first set of training data and a second set of training data and wherein each of the first set of training data and the second set of training data comprises a plurality of points representing the object;
building at least one statistical model having a set of parameters using the training data;
comparing the at least one statistical model to a 2-dimensional image of the portion of the object using the processor;
modifying at least one parameter of the set of parameters of the statistical model based on the comparison of the at least one statistical model to the 2-dimensional image of the portion of the object; and
passing the modified set of parameters representing the portion of the object through the statistical model.
10. The method according to claim 9 , wherein the training data includes data relating to portions of objects of the same type as the portion of the object that is capable of being represented by a statistical model.
11. The method according to claim 9 , wherein the statistical model is based on at least one of 2-dimensional shape, 2-dimensional texture, 3-dimensional shape and 3-dimensional texture.
12. The method according to claim 11 , wherein the 2-dimensional shape is based on a first plurality of points representing the first set of training data and a second plurality of points representing the second set of training data.
13. The method according to claim 11 , wherein the 2-dimensional texture is based on pixel values inside the 2-dimensional shape.
14. The method according to claim 13 , wherein the pixel values represent the colors red, green and blue.
15. The method according to claim 11 , wherein the 3-dimensional shape is based on a first plurality of points, a second plurality of points, a third plurality of points and a fourth plurality of points obtained from at least one of a 3-dimensional acquisition system and 2-dimensional images.
16. The method according to claim 11 , wherein the 3-dimensional texture is based on pixel values located between 3-dimensional points.