Method for real time tracking individual human face in complicated scene

A real-time tracking, complex scene technology, applied in instruments, character and pattern recognition, computer parts and other directions, can solve problems such as interference, inability to achieve tracking effect, affecting the accuracy of calculating pixel-like skin color probability, and achieve low computational complexity , the effect is stable

Active Publication Date: 2009-03-04
HAIAN SOOCHOW UNIV ADVANCED ROBOT RES INST
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AI Technical Summary

Problems solved by technology

However, in the process of performing histogram statistics on the search area by the H color channel, it is susceptible to the interference of background pixels in the search area, which affects the accuracy of calculating the probability of pixel-like skin color, and thus cannot achieve a good tracking effect

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  • Method for real time tracking individual human face in complicated scene
  • Method for real time tracking individual human face in complicated scene
  • Method for real time tracking individual human face in complicated scene

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Embodiment Construction

[0041] A preferred embodiment of the present invention is described as follows in conjunction with accompanying drawing: See figure 1 , a real-time tracking method for a single face in a complex scene, the steps include:

[0042] (1) Picture preprocessing: perform image linear transformation and Gaussian template filtering on the picture captured by the video;

[0043] (2) Face detection using skin color features: use the aggregation of skin color in the YCrCb color space to detect faces in the CrCb channel, and use morphological operations to initially remove the detected noise;

[0044](3) Elimination of the skin-like area: for the skin-like area in the scene, combined with the face area and geometric features to further eliminate, calculate the centroid of the face area, and set the initial search area centered on it;

[0045] (4) Face tracking: The face detection result is used as a new back projection image, and the continuous adaptive mean shift method is used to realiz...

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Abstract

The invention relates to a method for tracing the face of a single person in real time in complex scenes. The method comprises the following steps: (1) pretreating frames: linearly transforming the frames captured by a video and filtrating waves with Gaussian templates; (2) detecting the face by adopting complexion features: detecting the face by adopting the convergence of complexion in YCrCb colored space and morphologic operation of the face; (3) elimination of areas similar to the complexion: elimination of non-face areas similar to complexion in combination with the face area and the face geometrical features to get a perfect face area before the barycenter of the face area is computed with the perfect face area and the initial search area is set around the barycenter; (4) tracing the face: tracing the face by adopting the continuous adaptive mean deflection method with the face detection results as novel back projection drawings and features. In the method, the face is abstracted and tracked in combination with multiple features; the effects are stable and the complexity of computation is low. The method can be widely applied in the fields of video monitoring, man computer interaction interfaces and so on.

Description

technical field [0001] The invention relates to the fields of man-machine interface interaction and video monitoring, especially the real-time tracking of a single human face in complex scenes. Specifically, it is a continuous mean shift method that comprehensively considers multiple features and utilizes a new type of back-projection graph. Background technique [0002] In applications such as human-computer interaction and video surveillance, as one of the salient features for identifying personal identities, the detection and tracking of human faces will directly affect the overall performance of the system. For decades, countless scholars have done extensive research and discussion on the problem of face tracking, which are mainly divided into: methods based on face models, based on feature matching, based on motion information and based on skin color. However, due to the influence of many factors such as head rotation, lighting, shadows, and occluders, it has always be...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 寇超白琮陈泉林王华红王少波
Owner HAIAN SOOCHOW UNIV ADVANCED ROBOT RES INST
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