Example-based head tracking
Example-based head tracking
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DOI：
10.1109/afgr.1996.557294
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发表时间：
1996-10
期刊：
影响因子：
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通讯作者：
Sourabh A. Niyogi;W. Freeman
中科院分区：
文献类型：
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作者：
Sourabh A. Niyogi;W. Freeman
我们想要估计人类头部的姿势。该估计涉及从输入图像到输出参数描述的非线性映射。我们通过训练集中的样本来表征映射，输出输入最近的样本邻居的姿势。这是矢量量化，其修改是我们将输出参数代码与每个量化的输入代码一起存储。为了高效地索引，我们使用了树形结构的矢量量化器(TSVQ)。我们根据汽车驾驶员面部监控的应用实例进行了设计选择。对存储数据的依赖超过了计算能力，这使得系统变得简单；高效的数据组织使系统变得快速。我们将位置跟踪和尺度跟踪结合在同一个矢量量化框架中，几乎不需要额外的计算成本。我们给出了一个在廉价工作站上运行的实时原型的合理实验结果。
We want to estimate the pose of human heads. This estimation involves a nonlinear mapping from the input image to an output parametric description. We characterize the mapping through examples from a training set, outputting the pose of the nearest example neighbor of the input. This is vector quantization, with the modification that we store an output parameter code with each quantized input code. For efficient indexing, we use a tree-structured vector quantizer (TSVQ). We make design choices based on the example application of monitoring an automobile driver's face. The reliance on stored data over computation power allows the system to be simple; efficient organization of the data allows it to be fast. We incorporate tracking in position and scale within the same vector quantization framework with virtually no cost in added computation. We show reasonable experimental results for a real-time prototype running on an inexpensive workstation.