Realization of face contour tracking by GVF Snake and grey prediction

ZHOU Zhi-yu; YANG Wei-cheng; WANG Ya-ming; ZHANG Jian-xin; ZHENG Lei

doi:10.3788/OPE.20111911.2744

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Realization of face contour tracking by GVF Snake and grey prediction

Article | 更新时间：2020-08-12

- Realization of face contour tracking by GVF Snake and grey prediction
- Optics and Precision Engineering Vol. 19, Issue 11, Pages: 2744-2752(2011)
- 作者机构：
  
  1. 浙江理工大学信息电子学院,浙江杭州,310018
  2. 浙江理工大学机械与自动控制学院,浙江杭州,310018
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111911.2744
  CLC： TP391.4-4
- Received：09 May 2011，
  
  Revised：21 June 2011，
  
  Published Online：25 November 2011，
  
  Published：25 November 2011
- 稿件说明：
移动端阅览
周志宇, 杨卫成, 汪亚明, 张建新, 郑磊. 应用梯度矢量流Snake和灰预测的人脸轮廓跟踪[J]. 光学精密工程, 2011,19(11): 2744-2752

ZHOU Zhi-yu, YANG Wei-cheng, WANG Ya-ming, ZHANG Jian-xin, ZHENG Lei. Realization of face contour tracking by GVF Snake and grey prediction[J]. Editorial Office of Optics and Precision Engineering, 2011,19(11): 2744-2752
周志宇, 杨卫成, 汪亚明, 张建新, 郑磊. 应用梯度矢量流Snake和灰预测的人脸轮廓跟踪[J]. 光学精密工程, 2011,19(11): 2744-2752 DOI： 10.3788/OPE.20111911.2744.

ZHOU Zhi-yu, YANG Wei-cheng, WANG Ya-ming, ZHANG Jian-xin, ZHENG Lei. Realization of face contour tracking by GVF Snake and grey prediction[J]. Editorial Office of Optics and Precision Engineering, 2011,19(11): 2744-2752 DOI： 10.3788/OPE.20111911.2744.

摘要

为了提高动态图像序列中人脸轮廓跟踪时梯度矢量流(GVF)Snake算法的实时性

同时解决人脸跟踪中的遮挡问题

提出了GVF Snake和单变量一阶灰色模型GM(1

1)相结合的人脸轮廓提取方法。该方法首先利用人脸运动信息和肤色模型粗略地检测出运动人脸轮廓

然后采用GVF Snake算法将人脸轮廓精确地提取出来

从而有效解决GVF Snake算法的初始化问题。根据人脸轮廓运动的整体性

利用GM(1

1)模型预测人脸轮廓质心的位置

并以预测位置作为GVF Snake的迭代依据

同时将GVF Snake提取的人脸轮廓质心位置作为下一帧图像GM(1

1)模型的预测依据。存在遮挡时

则以GM(1

1)模型预测保持跟踪的连续性。实验结果表明

该算法跟踪的平均时间仅为GVF Snake算法的8.0%

平均跟踪误差仅为GVF Snake算法的31.2%

而且能更好地反映人脸轮廓的运动规律

跟踪实时性强

鲁棒性好。

Abstract

In order to improve the real-time performance of the Gradient Vector Flow Snake(GVF Snake) algorithm for face contour tracking in a dynamic image sequence and to overcome the occlusion problem in face tracking

a novel image extraction method combining the GVF Snake algorithm and the single variable first-order grey model GM(1

1) is proposed to extract the face contour. In this method

the moving face contour is roughly detected out firstly by using human motion information and the skin-color model

and then the accurate face contour is extracted by using the GVF Snake algorithm

by which the initialization problem of the GVF Snake algorithm is solued. For the integrity feature of face contour motion

the GM(1

1) model is used to predict the centroid position of face contour and then the position is used as the iteration basis of the GVF Snake algorithm. Meanwhile

the centroid position of face contour extracted with GVF Snake is taken as the prediction basis of the GM(1

1) model for the next frame. When the occlusion exists

the continuity of tracking can be held with the prediction of GM(1

1) model. Experimental results show that by proposed method

the average tracking time and the average tracking error are only 8.0% and 31.2% of those of the GVF Snake algorithm respectively. It can be concluded that this method can better reflect the motion law of face contour

and has strong real-time performance and good robustness.

关键词

Keywords

references

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