CPC Class H04N

A method of face detection to be performed by an apparatus including an image pickup module includes: obtaining a first image including image information of an object that is in focus; obtaining a pseudo distance between the image pickup module and the object when the first image is obtained by the obtaining; determining a first ratio of a plurality of ratios as a scaling value based on the pseudo distance; and performing face detection of the first image by changing the scaling value based on the first ratio.

Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of −24 g to +24 g with a high-range accelerometer having a range of −400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.

An adaptable eye artifact identification and correction method is disclosed. Eye artifacts are identified and classified based on color, severity, shape, eye location, and cause. Based on this classification, an eye artifact correction algorithm is selected from a series of eye artifact correction techniques. For minor artifacts, simple color correction techniques are deployed to restore the iris color and to drive the pupil to once again appear black. For severe eye artifacts face detection and metadata analysis are utilized to search the user's image collection for recent images of the subject without the eye artifact condition. Once located, these images provide eye color and shape information for use to replace the pixels expressing the eye artifact condition. The non-artifact eye images are used to provide the appropriate eye color and shape to correct the eye artifact condition for more severe eye artifacts.

An iris recognition camera system for mobile device includes a sensor and associated circuit, a lens and lighting sources including a lighting source element, a displaying light source element and IR LED light source elements, wherein the lighting sources are installed around the center of a camera lens with a certain clearance, and the lighting sources are attached on an FPCB and arranged on the four sides of the center of the camera lens and equipped with an FPCB cover for protection and a guiding mirror so that a user may conveniently acquire an image of his or her iris watching the image of his or her iris so as to identify and process only a living iris.