基于粒子滤波与改进GVF Snake的人手跟踪算法

doi:10.16183/j.cnki.jsjtu.2018.07.007

摘要/Abstract

摘要： 为实现在复杂背景下对人手进行准确、快速的位置跟踪与轮廓跟踪，并针对粒子滤波无法获取人手目标的准确信息与人手深凹区域获取难的问题，提出一种基于肤色自适应梯度矢量流主动轮廓(Gradient Vector Flow Snake, GVF Snake)模型的粒子滤波算法实现人手跟踪.该算法首先对粒子滤波得到的人手区域进行肤色灰度增强，弱化背景梯度信息，然后对该区域利用引入自适应梯度矢量流场和肤色自适应外部引导力的GVF Snake模型，获取人手的真实轮廓以及准确的系统观测和系统状态，减少了粒子退化的可能，完成了更加准确的位置跟踪.实验表明：在复杂、运动背景甚至大范围遮挡的情况下，该改进算法获得了更加准确的人手轮廓，同时对人手跟踪的实时性提升了13%，均方根误差降低了48%.

关键词: 人手跟踪, 人手轮廓, 梯度矢量流主动轮廓模型, 自适应, 粒子滤波

Abstract: To implement the hand tracking and contour tracking accurately and quickly in complex background, a novel algorithm for hand tracking with particle filter and skin color adaptive gradient vector flow snake (GVF snake) model is proposed. This algorithm especially applies to the extraction of deep concave region of hand contour, and overcomes the problem that particle filter can not obtain accurate information. Firstly, the hand region obtained by the particle filter is grayscale enhanced by skin color, weakening the background gradient information. And then the GVF snake model, with adaptive gradient vector flow field and adaptive external guidance force improved by skin color, is introduced to extract the real contour and modify the systematic observation and system state of particle filter. In this case, it can reduce the possibility of degradation of particles and realize hand tracking more accurately. The experimental results show that the proposed algorithm extracts more accurate contour of hand and improves real-time performance of human tracking by 13% and the root mean square error is reduced by 48%, under the conditions of complexity, moving background and even a wide range of occlusion.

Key words: hand tracking, hand contour, gradient vector flow snake (GVF snake) model, adaptiveness, particle filter

中图分类号:

TP 391.41

孙一奇，吴爱国，董娜，邵一哲. 基于粒子滤波与改进GVF Snake的人手跟踪算法[J]. 上海交通大学学报（自然版）, 2018, 52(7): 801-807.

SUN Yiqi,WU Aiguo,DONG Na,SHAO Yizhe. A Novel Algorithm for Hand Tracking with Particle Filter and Improved GVF Snake[J]. Journal of Shanghai Jiaotong University, 2018, 52(7): 801-807.

参考文献

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