3D CASCADED CONDENSATION TRACKING FOR MULTIPLE OBJECTS
3D CASCADED CONDENSATION TRACKING FOR MULTIPLE OBJECTS
复制标题
多个对象的 3D 级联冷凝跟踪
DOI：
10.2316/p.2010.678-104
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
T. Vetter
中科院分区：
文献类型：
--
作者：
Matthias Rätsch;Clemens Blumer;G. Teschke;T. Vetter
凝聚和小波近似缩减向量机（W-RVM）方法通过核心思想结合在一起，仅花费尽可能多的必要努力来容易区分特征空间的区域（凝聚）和测量位置（W-RVM），但大多数区域和位置具有高统计可能性来包含感兴趣的对象。我们通过调整W-RVM分类器来跟踪和改进冷凝方法来统一这两种方法。此外，我们利用Condensation来提取多维特征向量，并提供基于模板的三维相机场景跟踪。此外，我们引入了一个强大的多目标跟踪扩展的冷凝方法。针对多个物体的新3D级联冷凝跟踪（CCT）比最先进的检测方法快10倍以上。在我们的实验中，我们比较了不同的跟踪方法，使用主动双摄像头系统的人脸跟踪。
The Condensation and the Wavelet Approximated Reduced Vector Machine (W-RVM) approach are joined by the core idea to spend only as much as necessary effort for easy to discriminate regions (Condensation) and measurement locations (W-RVM) of the feature space, but most for regions and locations with high statistical likelihood to contain the object of interest. We unify both approaches by adapting the W-RVM classifier to tracking and refine the Condensation approach. Additionally, we utilize Condensation for abstract multi-dimensional feature vectors and provide a template based tracking of the three-dimensional camera scene. Moreover, we introduce a robust multi-object tracking by extensions to the Condensation approach. The new 3D Cascaded Condensation Tracking (CCT) for multiple objects yields a more than 10 times faster tracking than state-of-art detection methods. In our experiments we compare different tracking approaches using an active dual camera system for face tracking.