Accurate Segmentation for Infrared Flying Bird Tracking

作     者：ZHENG Hong HUANG Ying LING Haibin ZOU Qi YANG Hao 

作者机构：School of Automation Science and Electrical EngineeringBeihang University Department of Computer and Information ScienceTemple University School of Computer and Information TechnologyBeijing Jiaotong University Airport Research InstituteChina Academy of Civil Aviation Science and Technology 

出 版 物：《Chinese Journal of Electronics》 (电子学报(英文))

年 卷 期：2016年第25卷第4期

页      面：625-631页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：partly supported by the Beijing Higher Education Young Elite Teacher Project (No.YETP0546) 

主　　题：Object tracking Edge detection Segmentation Gaussian mixture model Markov random field(MRF) 

摘      要：Bird strikes present a huge risk for air vehicles,especially since traditional airport bird surveillance is mainly dependent on inefficient human *** improving the effectiveness and efficiency of bird monitoring,computer vision techniques have been proposed to detect birds,determine bird flying tra jectories,and predict aircraft takeoff *** bird with a huge deformation causes a great challenge to current tracking *** propose a segmentation based approach to enable tracking can adapt to the varying shape of *** approach works by segmenting object at a region of interest,where is determined by the object localization method and heuristic edge *** segmentation is performed by Markov random field,which is trained by foreground and background mixture Gaussian *** demonstrate that the proposed approach provides the ability to handle large deformations and outperforms the most state-of-the-art tracker in the infrared flying bird tracking problem.