计算机工程与科学2018，Vol.40Issue(4)：690-698,9.DOI:10.3969/j.issn.1007-130X.2018.04.016
基于改进KCF的跟踪注册方法
A tracking and registration method based on improved KCF
摘要
Abstract
Since 3D registration is easily affected by the environment and target tracking and detection algorithms are time-consuming with low precision,we propose a tracking and registration method based on an improved kernerlized correlation filter (I-KCF).The method includes four steps:(1) utilizing the regularized least squares classifier for sample training to obtain kernel correlation filter and position information;(2) searching scale kernel correlation filter and the maximum of position output to achieve the detection of the scale and position;(3) updating the model by referring to the MOSSE tracker;(4) adopting the oriented FAST and rotated BRIEF (ORB) to do feature extraction and matching,and then calculate the registration matrix.We utilize 6 sets of data in the Visual Tracker Benchmark datasets and video sequence to simulate.The results show that the I-KCF generally outperforms the KCF,tracking-learning-detection (TLD),structured output tracking with kernel (Struck) and compressive tracking (CT) in precision,success rate and efficiency when rotation,scale variation,partial occlusion,illumination or motion blur occurs.Besides,the target position is highly aligned with OpenGL cube registration,and the augmented reality (AR) system based on I-KCF is more real-time,stable and robust.关键词
KCF跟踪/I-KCF算法/ORB算法/三维注册/增强现实Key words
kernerlized correlation filter(KCF) tracking/I-KCF algorithm/ORB algorithm/3D registration/augmented reality分类
信息技术与安全科学引用本文复制引用
雍玖,王阳萍,雷晓妹..基于改进KCF的跟踪注册方法[J].计算机工程与科学,2018,40(4):690-698,9.基金项目
国家自然科学基金(61162016,61562057) （61162016,61562057）
甘肃省国际科技合作项目(144WCGA162) （144WCGA162）
兰州市人才创新创业科技计划项目(2014-RC-7) （2014-RC-7）
