SYSTEMS AND METHODS OF FACIAL AND BODY RECOGNITION, IDENTIFICATION AND ANALYSIS
Systems and methods for learning and recognizing features of an image are provided. A point detector identifies points in an image where there are two-dimensional changes. A geometric feature evaluator overlays at least one mesh on the image and analyzes geometric features on the at least one mesh. An internal calibrator transforms data from the point detector and the geometric feature evaluator into a three-dimensional point figure of the image, and a depth evaluator determines a final shape of the image. A three-dimensional object model of the image is constructed. The image could be a human face or body. An artificial intelligence unit learns and identifies a user's facial features including skull size, distance between eyes, and bone structure and body features including skeleton shape and body size. Exemplary systems and methods can construct and learn features of a human face based on a partial view where part of the face is covered. Systems and methods can unlock a mobile device based on recognition of the features of the user's face.
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;
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;
an artificial intelligence unit configured to learn and identify a user's facial features including skull size, distance between eyes, and bone structure, and the user's body features including skeleton shape and body size; and
at least one depth evaluator determining a final shape of the image.
2 . The system of claim 1 wherein the image is of a human face and a 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 two-dimensional changes comprise one or more of: corners, junctions, and vertices.
6 . The system of claim 1 wherein the system constructs a three-dimensional object model of the image.
7 . The system of claim 6 wherein the system constructs a three-dimensional object model of the image from a partial view of the image.
8 . 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.
9 . The system of claim 1 further comprising a neural network.
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;
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;
constructing a three-dimensional object model of the image; and
registering the three-dimensional object model in an image models database.
11 . The method of claim 10 further comprising querying whether the three-dimensional object model presents in the image models database.
12 . 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.
13 . The method of claim 12 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.
14 . The method of claim 10 wherein one or both of the identifying and constructing steps are performed based on a partial view of the image.
15 . The method of claim 13 wherein the recognition and unlocking are performed based on a partial view of the features of the user's face.
16 . The method of claim 10 further comprising storing as a reference data relating to the features of the user's face.
17 . A computer-implemented method of learning and recognizing features of an image of a human face, comprising:
performing image pixelation including high resolution pixelation-based facial mapping and low resolution pixelation-based facial mapping;
performing sideways facial mapping;
performing biometric facial mapping;
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; and
determining a final shape of the image.
18 . The method of claim 17 further comprising performing a study of a human body based on vector mapping.
19 . The method of claim 18 further comprising identifying clothing based on vector mapping.
20 . The method of claim 18 further comprising identifying accessories based on vector mapping.