Quick positioning method of facial feature points

Abstract

The invention discloses a quick positioning method of facial feature points. The quick positioning method comprises the following steps: 1) taking Haar-Like features as a basis, and adopting a trained cascaded classifier to successively detect a left eye and a right eye; 2) taking a detection result of the left eye and the right eye as the basis, obtaining the precise positions of the inner canthus point of the left eye and the inner canthus point of the right eye; 3) taking the inner canthus points and the distance between the inner canthus points as a criterion, applying a geometric feature of "Three Tings and Five Eyes" of the human eyes to quickly determine key feature points on the outer contour of a mouth and the outer contour of each eye, storing the points as a reference feature table to serve as a search reference of a next frame of feature points; and 4) taking a previous frame of a left-eye coordinate stored in the reference feature table as an initial position, taking inner canthus distance as the criterion, setting a search range of a current frame of human eyes at a ratio according to a geometry of a human face, repeating the steps 1) to 3), carrying out full-figure search again when the left eye can not be detected within a set search range, and repeating the steps 1) to 3). The quick positioning method can quickly and accurately position the facial feature points without a special device.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, and in particular relates to a method for rapidly locating facial feature points according to real-time positioning of specified feature points in facial video. Background technique [0002] At present, there are existing methods of judging the state of the eyes based on facial images, measuring the direction of the person's line of sight, and estimating the degree of arousal of the person. In order to judge the state of the eyes, it is necessary to correctly detect the eye feature points of the face image. In addition, when judging the awakening state of the vehicle driver, it is necessary to detect facial feature points in real time, including eye feature points and mouth feature points. [0003] For example, in Patent Document 1 (CN102254151A, a driver fatigue detection method based on facial video analysis), technologies such as facial feature point location ...

AI Technical Summary

Problems solved by technology

Although this method can accurately locate the feature points in most cases, the iterative matching process increases sharply with the increase of the number of feature points, and the matching time is too long, so it is not suitable for practical use.

[0006] Patent Document 2 uses a specific shape constraint on the detected eye edge image to detect the edge of the eye. There are two problems in practical application. One is that the fixed shape constraint is difficult to satisfy human eyes of different sizes and shapes at the same time, and the other is that The edge shape of the same human eye is greatly affected by different face poses. This method requires a special device proposed in Document 2 to ensure the reliability of the algorithm.

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