|本期目录/Table of Contents|

[1]骆绍烨,刘丽桑.基于改进Camshift的人脸跟踪算法[J].延边大学学报(自然科学版),2017,(02):144-149.
 LUO Shaoye,LIU Lisang.Face tracking algorithm based on improved Camshift[J].Journal of Yanbian University,2017,(02):144-149.
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基于改进Camshift的人脸跟踪算法()
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《延边大学学报(自然科学版)》[ISSN:1004-4353/CN:22-1191/N]

卷:
期数:
2017年02期
页码:
144-149
栏目:
基础科学研究
出版日期:
2017-07-20

文章信息/Info

Title:
Face tracking algorithm based on improved Camshift
作者:
骆绍烨1 刘丽桑2
1.莆田学院 信息工程学院, 福建 莆田 351100; 2.福建工程学院 信息科学与工程学院, 福建 福州 350118
Author(s):
LUO Shaoye1 LIU Lisang2
1.College of Information Engineering, Putian University, Putian 351100, China; 2.College of Information Science and Engineering, Fujian University of Technology, Fuzhou 350118, China
关键词:
人脸跟踪 Camshift 分块颜色直方图 Kalman滤波
Keywords:
face tracking Camshift block color histogram Kalman filter
分类号:
TP391.41
DOI:
-
文献标志码:
A
摘要:
研究了一种基于改进Camshift的人脸跟踪算法.该算法采用分块加权的直方图匹配方法增强人脸的辨识度,通过人脸形态约束筛选不合理的人脸形态变化,并结合Kalman滤波器预测修正跟踪人脸位置.实验表明,改进后的算法比经典Camshift算法有更强的抗肤色干扰能力和跟踪准确性.
Abstract:
The improved Camshift algorithm for face tracking is proposed, which enhances the identification of facial structure by using the block weighted color histogram in template matching, filtrates the unreasonable facial morphological change according to the face shape detection, predicts and amends the accuracy of face tracking through Kalman filter. Experimental results prove the improved algorithm become stronger interference ability, higher tracking accuracy than the classical Camshift algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-03-31 作者简介: 骆绍烨(1982—),男,讲师,研究方向为计算机视觉、信息检索.
基金项目: 国家自然科学基金资助项目(81373552); 莆田市科技计划项目(2015G2014)
更新日期/Last Update: 2017-06-20