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ICONDENSATION: Unifying low-level and high-level tracking in a stochastic framework

机译:图标:在随机框架中统一低层和高层跟踪

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Yracking research has diverged into two camps; low-level approaches which are typically fast and robust but provide little fine-scale information, and high-level approaches which track complex deformations in high-dimensional spaces but must trade off speed against robustness. Real-time high-level systems perform poorly in clutter and initialisation for most high-level systems is either performed manually or by a separate module. This paper resents a new technique to combine low- and high-level information in a consistent probabilistic framework, using the statistical technique of importance sampling combined with the Condensation algorithm. The general framework, which we term Icondensation, is described, and a hand tracker is demonstrated which combines colour blob-tracking with a contour model. The resulting tracker is robust to rapid motion, heavy clutter and hand-coloured distractors, and re-initialises automatically. The system runs comfortably in real time on an entry-level desktop workstation.
机译:激流的研究分为两个阵营。低级方法通常快速且健壮,但提供的精细信息很少,而高级方法则跟踪高维空间中的复杂变形,但必须在速度与鲁棒性之间进行权衡。实时高级系统在混乱情况下表现不佳,大多数高级系统的初始化是手动执行或由单独的模块执行。本文对重要性抽样的统计技术与压缩算法相结合的一种新技术,将低级和高级信息组合在一个一致的概率框架中感到不满。描述了我们称为Icondensation的通用框架,并展示了一个手跟踪器,该手跟踪器将颜色斑点跟踪与轮廓模型结合在一起。生成的跟踪器对于快速运动,杂乱无章和手工着色的干扰器具有鲁棒性,并且会自动重新初始化。该系统可以在入门级台式工作站上实时舒适地运行。

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