Head posture estimation interest point detection method fusing depth and gray scale image characteristic points

Abstract

The invention relates to a head posture estimation interest point detection method fusing depth and gray scale image characteristic points. The method comprises the following steps: extracting the characteristic points of a depth image; extracting the characteristic points of a gray scale image; fusing the characteristic points of the depth image and the gray scale image. The characteristic point detected on the basis of the depth image and the characteristic point detected on the basis of the gray scale image are combined to form certain characteristic points which are positioned accurately and are high in robustness, thereby inheriting the advantage of the detection of different characteristic points of the depth image and the gray scale image, and realizing maximum and rapid detection of characteristic points with great surface variations in the depth image and a pupil area with a great gray scale value in the gray scale image. In particular, a calculation mode for correcting a calculated Haar-like characteristic value in the depth image is provided, the finally-extracted characteristics have certain spatial rotation invariability, and the true values of human face characteristic points can be approached under the situation of large-angle rotation, thereby increasing the final characteristic point detection accuracy, and shortening the detection time.

Description

technical field [0001] The present invention relates to the technical fields of digital image processing and computer vision, in particular to a head pose estimation interest point detection method based on fusion of depth and grayscale images. Background technique [0002] Head pose estimation is an important part of the analysis of human behavior. It can be used as a result for somatosensory games, driver fatigue driving monitoring, and as a preprocessing process to improve the accuracy of identity authentication and facial expression recognition. Among them, the use of head interest points to analyze head pose is an important branch of head pose estimation, and the accurate and fast positioning of feature points directly determines the accuracy and speed of head pose estimation. However, due to the resolution of the camera itself, the complexity of the background environment, lighting changes, skin color and other factors, accurate and fast detection of feature points has...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a head pose estimation interest point detection method based on the fusion of depth and grayscale images, which combines the feature points detected based on the depth image with the feature points detected based on the grayscale image, and finally forms some Accurately locate feature points with strong robustness, effectively solve the problem of inaccurate feature point detection results and poor robustness in existing algorithms, which cause low accuracy of head pose estimation due to error accumulation

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