Face detection and tracking method based on embedded system

Abstract

The invention discloses a face detection and tracking method based on an embedded system, which comprises: an image preprocessing step which comprises downsampling and calculating a gray integral figure; a face detection step in which a large number of non-human face windows are eliminated by a color proportion judgment method and an eye grey characteristic judgment method, then the remaining small number of windows are detected and positioned by a face classifier based on Adaboost algorithm; and a face tracking step in which a simplified method of combining elliptical contour information andcolor histogram information is used. The face detection and tracking method of the invention greatly reduces the computation of face detection, can be applied to electronic products employing the embedded system such as a digital camera, a digital video camera and a mobile phone.

Description

technical field [0001] The invention relates to face detection and tracking technology, in particular to a fast face detection and real-time tracking method based on an embedded system. Background technique [0002] The exploration of face detection and recognition problems began in the late 1980s and early 1990s, and many countries launched research on face detection. In 2001, Viola et al. proposed a waterfall classifier based on Haar features and using the Adaboost method. It adopted a hierarchical processing method, which greatly improved the detection speed, and was recognized as the best frontal face detection method in recent years. The problem of frontal face detection has been basically solved in theory. [0003] Although the research on face detection and recognition technology has made great progress, under the mature general platform based on PC WINDOWS, there is no need to consider too many technical bottlenecks such as computing speed and data storage, and ther...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a face detection and tracking method based on an embedded system, so that face detection and tracking can be applied to digital cameras, digital cameras, mobile phones and other electronic products that use embedded systems to solve the problem of embedded systems. Due to factors such as slow DSP processing speed, limited memory resources, and poor platform openness, the system cannot realize the technical problems of face detection and tracking

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