PFAAM是一种基于主动外观模型的粒子滤波算法，具有鲁棒性和精确性

Fourth Canadian Conference on Computer and Robot Vision (CRV '07) Pub Date : 2007-05-28 DOI:10.1109/CRV.2007.50

S. Fleck, M. Hoffmann, K. Hunter, A. Schilling

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引用次数: 9

摘要

基于模型的跟踪是当今许多系统的关键组成部分，例如在视频监控或人机接口(HCI)中。我们的方法由粒子滤波器(PFs)和主动外观模型(AAMs)的组合组成:PFAAM。它结合了PFs的鲁棒性和aam的精度。给出了实验结果。与标准aam和仅使用aam作为线索(即不使用局部优化循环)的PFAAM相比，PFAAM表现出卓越的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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PFAAM An Active Appearance Model based Particle Filter for both Robust and Precise Tracking

Model based tracking is one key component of many systems today, e.g. within video surveillance or human computer interfaces (HCI). Our approach consists of a combination of particle filters (PFs) and active appearance models (AAMs): the PFAAM. It combines the robustness of PFs with the precision of AAMs. Experimental results are given. PFAAM shows superior perfomance compared to both standard AAMs and PFs using AAMs as cues only, i.e. without using a local optimization loop.

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Fourth Canadian Conference on Computer and Robot Vision (CRV '07)

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