Method of performing a user-specific and device-specific calibration of point of gaze estimation
A method of performing a user-specific and device-specific calibration of point of gaze estimation comprising a user's mobile device, a calibration target displayer, a built-in camera video data recorder, a perspective transform matrix process, a calibration data set splitter, and a support vector regression calculator by having a built-in camera process gaze in absolute measurement terms based on a series of successive data points based on a non-static marker.
1. A method of calibrating point of gaze estimation, comprising the steps:
providing a calibration application;
providing a user device;
wherein said user device comprises a display and a user-facing camera;
wherein said calibration application runs on said user device;
wherein said calibration application causes to be displayed on said display a non-static calibration marker;
prompting a user to look at said non-static calibration marker by displaying said non-static calibration marker on said display;
capturing one or more images of said user as said user is prompted to look at said non-static calibration marker;
recording a series of coordinates corresponding to where said non-static calibration marker appears on said display when said one or more images of said user are captured;
wherein said series of coordinates comprise a series of target ground truth positions for said non-static calibration marker, which comprise a target ground truth position data;
generating a calibration data set by matching said target ground truth position data with said captured images; and
processing said calibration data set by a perspective transform matrix process into a 3×3 transform matrix.
2. The method of calibrating point of gaze estimation of claim 1 , wherein said target ground truth position data comprises one or more vertices.
3. The method of calibrating point of gaze estimation of claim 2 , wherein said one or more vertices comprise four vertices.
4. The method of calibrating point of gaze estimation of claim 3 , wherein said four vertices comprise a first vertex, a second vertex, a third vertex, and a fourth vertex; and
wherein said one or more vertices, if connected, form a quadrangle.
5. The method of calibrating point of gaze estimation of claim 4 , wherein said first vertex is a top left display corner;
wherein said second vertex is a top right display corner;
wherein said third vertex is a bottom left display corner; and
wherein said fourth vertex is a bottom right display corner.
6. The method of calibrating point of gaze estimation of claim 5 , wherein where said user is determined to have been looking is a look point;
dividing an input cloud into four quadrants, wherein said input cloud comprises said look points.
7. The method of calibrating point of gaze estimation of claim 6 , wherein a center point of said four quadrants comprises a center of mass of said look points.
8. The method of calibrating point of gaze estimation of claim 7 , wherein said vertices are determined to produce a quadrangle of the largest area for a given quadrant.
9. The method of calibrating point of gaze estimation of claim 8 , wherein said user comprises one or more user characteristics;
wherein said one or more user characteristics comprise gender, skin color, eye shape, age, hair, background color, and lighting conditions; and
wherein said user characteristics are used as factors in said perspective transform matrix.
10. A method of calibrating point of gaze estimation, comprising the steps:
providing a calibration application;
providing a user device;
wherein said user device comprises a display and a user-facing camera;
wherein said calibration application runs on said user device;
wherein said calibration application causes to be displayed on said display a non-static calibration marker;
prompting a user to look at said non-static calibration marker by displaying said non-static calibration marker on said display;
capturing one or more images of said user as said user is prompted to look at said non-static calibration marker;
recording a series of coordinates corresponding to where said non-static calibration marker appears on said display when said one or more images of said user are captured;
wherein said series of coordinates comprise a series of target ground truth positions for said non-static calibration marker, which comprise a target ground truth position data;
generating a calibration data set by matching said target ground truth position data with said captured images;
processing said calibration data set by a perspective transform matrix process into a 3×3 transform matrix;
wherein said target ground truth position data comprises one or more vertices;
wherein said one or more vertices comprise four vertices;
wherein said four vertices comprise a first vertex, a second vertex, a third vertex, and a fourth vertex;
wherein said one or more vertices, if connected, form a quadrangle;
wherein said first vertex is a top left display corner;
wherein said second vertex is a top right display corner;
wherein said third vertex is a bottom left display corner;
wherein said fourth vertex is a bottom right display corner;
wherein where said user is determined to have been looking is a look point;
dividing an input cloud into four quadrants, wherein said input cloud comprises said look points;
wherein a center point of said four quadrants comprises a center of mass of said look points;
wherein said vertices are determined to produce a quadrangle of the largest area for a given quadrant.