Calculation method of line-of-sight direction based on analysis and match of iris contour in human eye image
First Claim
1. A calculation method of line-of-sight direction based on analysis and match of iris contour in human eye image, comprising the following steps:
- (1) constructing a sphere eyeball model, traversing eyeball orientations with different physical feasibilities, generating 2D virtual eyeball appearances with different orientations by geometric calculation, and storing all the eyeball orientations and corresponding virtual eyeball appearance data in a dataset for use in specific applications;
(2) during application, firstly shooting a facial image of a user, fixing on a left-eye or right-eye region, pre-treating a human eye image, completing brightness correction and extracting pixels on iris edges in the human eye image;
(3) regarding the shot and pre-treated human eye image and the virtual eyeball appearance data in the dataset, matching the human eye image with the virtual eyeball appearance data via a matching optimization algorithm of the human eye image and the virtual eyeball appearance data, wherein a matching result determines an orientation and a position of the eyeball which best match with the human eye image; and
(4) regarding continuously shot human eye images, further conducting joint optimization on the basis of the eyeball appearance matching in step (3), on the condition that a central position of the eyeball remains unchanged, or that the human eye images have been aligned, and precisely and simultaneously calculating 3D line-of-sight direction corresponding to each image;
wherein a method for the joint optimization in step (4), and the method for accurately calculating the 3D line-of-sight direction corresponding to each image simultaneously are as follows, under the assumption that central position of the eyeball remains unchanged or has been aligned when the images shot, conducting the matching of the human eye images with the virtual eyeball appearance in step (3), and calculating the eyeball orientation corresponding to each human eye image and the coordinates of the central position of the eyeball;
excluding the central coordinates of the eyeball with obvious deviation therein, and conducting weighting calculation of standard coordinates of the eyeball center using the remaining coordinates; and
individually carrying on with the optimization in step (3), while adding one optimization constraint, namely, coinciding the matched eyeball central coordinates as much as possible with the standard eyeball central coordinates, and updating the calculation results as the eyeball orientations in the human eye images, namely, the final results of the 3D line-of-sight direction.
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Abstract
The invention provides a calculation method of line-of-sight direction based on analysis and match of iris contour in human eye image, including: a data driven method, for stable calculation of 3D line-of-sight direction via inputting human eye image to be matched with synthetic data of virtual eyeball appearance; two novel optimization matching criterions of eyeball appearance, which effectively reduce effects of uncontrollable factors, such as image scaling and noise on results; a joint optimization method, for the case of continuously shooting multiple human eye images, to further improve calculation accuracy. One application of the invention is virtual reality and human computer interaction which is under the principle that shooting eye images of a user and calculating line-of-sight direction of user to enable interaction with intelligent system interface or virtual realistic object. The invention can be widely used in training, games and entertainment, video surveillance, medical care and other fields.
13 Citations
6 Claims
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1. A calculation method of line-of-sight direction based on analysis and match of iris contour in human eye image, comprising the following steps:
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(1) constructing a sphere eyeball model, traversing eyeball orientations with different physical feasibilities, generating 2D virtual eyeball appearances with different orientations by geometric calculation, and storing all the eyeball orientations and corresponding virtual eyeball appearance data in a dataset for use in specific applications; (2) during application, firstly shooting a facial image of a user, fixing on a left-eye or right-eye region, pre-treating a human eye image, completing brightness correction and extracting pixels on iris edges in the human eye image; (3) regarding the shot and pre-treated human eye image and the virtual eyeball appearance data in the dataset, matching the human eye image with the virtual eyeball appearance data via a matching optimization algorithm of the human eye image and the virtual eyeball appearance data, wherein a matching result determines an orientation and a position of the eyeball which best match with the human eye image; and (4) regarding continuously shot human eye images, further conducting joint optimization on the basis of the eyeball appearance matching in step (3), on the condition that a central position of the eyeball remains unchanged, or that the human eye images have been aligned, and precisely and simultaneously calculating 3D line-of-sight direction corresponding to each image; wherein a method for the joint optimization in step (4), and the method for accurately calculating the 3D line-of-sight direction corresponding to each image simultaneously are as follows, under the assumption that central position of the eyeball remains unchanged or has been aligned when the images shot, conducting the matching of the human eye images with the virtual eyeball appearance in step (3), and calculating the eyeball orientation corresponding to each human eye image and the coordinates of the central position of the eyeball;
excluding the central coordinates of the eyeball with obvious deviation therein, and conducting weighting calculation of standard coordinates of the eyeball center using the remaining coordinates; and
individually carrying on with the optimization in step (3), while adding one optimization constraint, namely, coinciding the matched eyeball central coordinates as much as possible with the standard eyeball central coordinates, and updating the calculation results as the eyeball orientations in the human eye images, namely, the final results of the 3D line-of-sight direction. - View Dependent Claims (2, 3, 4, 5, 6)
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Specification