Learning and evaluating visual features for pose estimation
Learning and evaluating visual features for pose estimation
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学习和评估姿势估计的视觉特征
DOI：
10.1109/iccv.1999.790419
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
G. Dudek
中科院分区：
文献类型：
--
作者：
Robert Sim;G. Dudek
我们提出了一种学习一组视觉标志的方法，这对于姿势估计很有用。地标学习机制被设计为适用于广泛的环境，并可推广到计算姿态估计的不同方法。最初，每个地标被检测为独特性度量的焦点极值，并由用于匹配的主成分编码表示。可以使用通用参数化方法对观察到的地标的属性进行参数化，然后根据它们对姿态估计的效用进行评估。我们提供实验证据来证明该方法的实用性。
We present a method for learning a set of visual landmarks which are useful for pose estimation. The landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different approaches to computing a pose estimate. Initially, each landmark is detected as a focal extremum of a measure of distinctiveness and represented by a principal components encoding which is exploited for matching. Attributes of the observed landmarks can be parameterized using a generic parameterization method and then evaluated in terms of their utility for pose estimation. We present experimental evidence that demonstrates the utility of the method.