Computer implemented methods and devices for determining dimensions and distances of head features

A device, comprising:

• means for providing an image of a head of a person,
• means for identifying a plurality of features in the image including a landmark,
• means for calculating a probability distribution for a number of pixels per millimeter for the image based on a machine learning approach including a Gaussian process, wherein the probability distribution for the number of pixels per millimeter for the image is further based on pixel dimensions of at least two features of the plurality of features and a respective probability distribution of a real dimension for each of the at least two features of the plurality of features, and
• means for estimating a real distance between at least one target feature of the plurality of features and a camera device used for capturing the image based on the probability distribution for the number of pixels per millimeter for the image and a pixel dimension of at least one feature of the plurality of features,
• wherein the machine learning approach includes extracting an image gradient orientation from training images and aligning respective pixels of the landmark for the training images.

A computer implemented method for estimating or determining dimensions or distances of head features, the method comprising:

• providing an image of a head of a person;
• identifying at least two features and at least one target feature in the image;
• obtaining a probability distribution for a number of pixels per millimeter for the image based on a machine learning approach including a Gaussian process based on prior information, wherein the probability distribution for the number of pixels per millimeter for the image is further based on pixel dimensions of the at least two features and a respective probability distribution of a real dimension for each of the at least two features;
• and
• estimating at least one of a real dimension of the at least one target feature or a real distance between the at least one target feature and a camera device used for capturing the image based on the probability distribution for the number of pixels per millimeter for the image and a pixel dimension of at least one feature in the image,
• wherein the at least two features are different from the at least one target feature,
• wherein the prior information includes information about size distributions of the at least two features, and
• wherein the information about the size distributions is obtained from a plurality of heads.

A computer implemented method for estimating or determining dimensions or distances of head features, the method comprising:

• providing an image of a head of a person;
• identifying a plurality of features in the image;
• calculating a probability distribution for a number of pixels per millimeter for the image based on a machine learning approach including a Gaussian process;
• estimating at least one of a real dimension of at least one target feature of the plurality of features or a real distance between the at least one target feature of the plurality of features and a camera device used for capturing the image based on the probability distribution for the number of pixels per millimeter and a pixel dimension of at least one feature of the plurality of features,
• wherein the at least one target feature of the plurality of features is an interpupillary distance;
• and
• updating a multivariate Gaussian distribution,
• wherein the updating is performed according to p(ƒ|X, PD)=p(PD|ƒ, X) p(ƒ|X)/∫p(PD|ƒ)p(ƒ|X)dƒ′,
• wherein f is the multivariate Gaussian distribution, X represent the plurality of features, PD is the interpupillary distance, and p is a probability function.