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用对称群的傅立叶分析解决多目标跟踪中的数据关联问题

Solving the data association problem in multi-object tracking by Fourier analysis on the symmetric group
课程网址: http://videolectures.net/aispds08_kondor_sdap/  
主讲教师: Risi Kondor
开课单位: 伦敦大学学院
开课时间: 2008-08-08
课程语种: 英语
中文简介:
除了对单个目标的位置进行建模外,多目标跟踪还必须解决目标与相应轨迹匹配的组合问题。一般情况下,保持n的概率分布!可能性显然是不可行的,而仅仅维持一阶边际矩阵的n倍;是一个非常贫乏的表现。在本文中,我们解释了如何利用对称群上的调和分析理论来得到一个近似的层次结构来提高对这个问题的保真度。重要的是,这种有限带宽的近似方法不仅在理论上是合理的,而且它们还允许根据Clausen&rsquo’s FFT对对称组的一些观点进行有效的观测更新。
课程简介: In addition to modeling the position of individual targets, multi-object tracking must also address the combinatorial problem of matching objects to corresponding tracks. In general, maintaining a probability distribution over all n! possibilities is clearly infeasible, while just maintaining an n×n matrix of “first order marginals” is a very impoverished representation. In this work we explain how to harness the theory of harmonic analysis on the symmetric group to get a hierarchy of approximations of increasing fidelity to this problem. Importatantly, not only are such band-limited approximations theoretically well justifiable, but they also admit efficient observations updates based on some ideas from Clausen’s FFT for the symmetric group.
关 键 词: 对称群; 傅立叶; 多目标跟踪; 数据关联
课程来源: 视频讲座网
最后编审: 2021-02-04:nkq
阅读次数: 31