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基于模糊规则自适应弹性图像配准的视频跟踪

Visual Tracking Based on Fuzzy-Inference-Rule Adaptive Elastic Image Registration
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摘要 把形变视频跟踪看作一个动态图像配准问题,基于已有的模糊规则自适应学习弹性图像配准方法,提出了一个具有较好鲁棒性的视频跟踪算法。较之于一些经典的跟踪算法,提出的新算法显示出了更鲁棒的跟踪效果。 By taking deformal visual tracking as the procedure of active image registration,the existing fuzzy-inference-rule adaptive elastic image registraion is used to develop a much more robust visual tracking algorithm.Compared with two classical visual tracking algorithms,the proposed algorithm demonstrates a promising performance.
作者 邓赵红 王士同
机构地区 江南大学信息工程学院 浙江大学CAD&CG国家重点实验室
出处 《江南大学学报（自然科学版）》 CAS 2010年第2期127-132,共6页 Joural of Jiangnan University (Natural Science Edition)　
基金 国家自然科学基金项目(60903100) 江苏省自然科学基金项目(BK2009067) 浙江大学CAD&CG国家重点实验室基金项目
关键词 弹性图像配准 模糊推理规则 移动估计 自适应学习 形变视频跟踪 elastic image registration fuzzy inference rule motion estmation adaptive learning deformal visual tracking
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献19

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二级参考文献121

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共引文献514

江南大学学报（自然科学版）
2010年 第2期

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