Systems and methods of facial and body recognition, identification and analysis

1. A system for learning and recognizing features of an image, comprising:

at least one point detector identifying points in an image where there are two-dimensional changes including one or more of: corners, junctions, and vertices;

at least one geometric feature evaluator overlaying at least one mesh on the image and analyzing geometric features on the at least one mesh;

at least one internal calibrator transforming data from the point detector and the geometric feature evaluator into a three-dimensional point figure of the image;

at least one depth evaluator determining a final shape of the image;

an artificial intelligence unit configured to learn a user's facial and body features;

a neural network providing data and performing image pixelation including high resolution pixelation-based facial mapping, low resolution pixelation-based facial mapping, and classifier training; and

an expert system having as its input the data from the neural network and being configured to read the data from the neural network and identify unique features of a user's face or body and map the unique features into a database.

2. The system of claim 1 wherein the image is of a human face or human body.

3. The system of claim 1 wherein the point detector and the geometric feature evaluator identify points based on geodesic distance between vertices in the mesh.

4. The system of claim 1 wherein the geometric feature evaluator uses stereo vision.

5. The system of claim 1 wherein the system is housed in a mobile device and is configured to lock or unlock the mobile device upon identification of the user's facial or body features.

6. The system of claim 1 wherein the expert system computes physical relations and ratios of unique facial and body features comprising one or more of: distance and depth.

7. The system of claim 1 wherein the neural network further performs portrait wide facial mapping.

8. The system of claim 7 wherein the expert system further performs sideways facial mapping.

9. The system of claim 8 wherein the expert system further performs biometric facial mapping.

10. A computer-implemented method of learning and recognizing features of an image, comprising:

identifying points in an image where there are two-dimensional changes;

overlaying at least one mesh on the image and analyzing geometric features on the at least one mesh;

transforming data relating to the points and geometric features into a three-dimensional point figure of the image;

determining a final shape of the image;

providing data from a neural network as input to an expert system, the expert system reading the data from the neural network, identifying unique features of a user's face or body, and mapping the unique features into a database;

performing image pixelation including high resolution pixelation-based facial mapping and low resolution pixelation-based facial mapping; and

constructing a three-dimensional object model of the image from a partial view of the image.

11. The method of claim 10 wherein the image is of a human face or body and further comprising learning features of a user's face or body.

12. The method of claim 11 further comprising identifying the features of the human face and unlocking a mobile device based on recognition of the features of the user's face.

13. The method of claim 11 wherein the learning is performed based on a partial view of the user's face.

14. The method of claim 12 wherein the recognition and unlocking are performed based on a partial view of the features of the user's face.

15. The method of claim 10 further comprising storing as a reference data relating to the features of the user's face.