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基于分类的视觉跟踪算法研究
Alternative TitleResearch on Classification Based Visual Tracking Algorithm
陈铎文
Subtype工学硕士
Thesis Advisor唐明
2009-06-02
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword分类 跟踪 图像片 相对空间 距离学习 稳定性 准确度 Classification Tracking Image Patch Boosting Relative Space Local Distance Accuracy Stability
Abstract视觉跟踪技术,在诸如视频监视、智能交通、人机交互、视频压缩等方面具有非常广泛的应用前景,因此一直是计算机视觉方向的研究热点之一。本文在总结目前已有的视觉跟踪算法的基础上,提出两种基于分类的视觉跟踪算法。本文的主要工作归纳如下三个方面:1)对视觉跟踪算法,尤其是近五年来基于分类的跟踪算法发展进行综述,分析这些方法的优缺点以及适用范围,对于后续工作中展开新算法的研究和实验提供参考与借鉴;2)在基于分类的跟踪算法整体框架下,专注于设计精确而稳定的分类器。提出两种不同的解决思路,一种是基于增强(Boosting)相对子空间的分类器融合,另一种是基于局部距离学习;3)设计出一组评价跟踪算法有效性的度量准则,通过对多种跟踪算法的实验比较,显示我们的跟踪算法在关键性能上的优势。
Other AbstractThe technology of visual tracking has promising future in applications of video surveillance, intelligent traffic control, human-computer interaction, video compress etc. It is a popular research topic in Computer Vision. In this dissertation, we focus on the fundamental research of classification based tracking algorithm. Through reviewing recent tracking algorithms, we propose two classification based algorithms. And the content of this dissertation is summarized as below. Firstly, most of tracking algorithms, especially those published in recent five years are reviewed. Some are analyzed with both advantages and disadvantages, which helps us to make improvements and devise our own algorithms. Secondly, under the classification based tracking framework, we focus on constructing accurate and robust classifiers. Two methods are proposed, one is boosting the relative spaces, and the other is based on local distance learning. Thirdly, a group of criteria for measuring the accuracy and stability of tracking algorithm is proposed initially. We do experiments on many sequences with different tracking algorithms. Through comparison based on our criteria, we show the superior performance of our tracking algorithms.
shelfnumXWLW1398
Other Identifier200628014628027
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7485
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
陈铎文. 基于分类的视觉跟踪算法研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2009.
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