Isophote properties as features for object detection
Isophote properties as features for object detection
复制标题
等照度属性作为目标检测的特征
DOI：
10.1109/cvpr.2005.196
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
M. Reinders
中科院分区：
文献类型：
--
作者：
J. Lichtenauer;E. Hendriks;M. Reinders
通常，对象检测直接在（归一化）灰度值或灰度基元（如梯度或Haar特征）上执行。在这种情况下，学习描述对象结构的灰度基元之间的关系是分类器的全部责任。我们建议在预处理步骤中应用更多关于图像结构的知识，通过计算局部等照度线方向和曲率，以便为分类器提供更多信息的图像结构特征。然而，一个周期性的特征空间，像方向，是不适合常见的分类方法。因此，我们将方向分为两个更合适的部分。实验表明，等照度线特征比强度、梯度和类Haar特征具有更好的检测性能。
Usually, object detection is performed directly on (normalized) gray values or gray primitives like gradients or Haar-like features. In that case the learning of relationships between gray primitives, that describe the structure of the object, is the complete responsibility of the classifier. We propose to apply more knowledge about the image structure in the preprocessing step, by computing local isophote directions and curvatures, in order to supply the classifier with much more informative image structure features. However, a periodic feature space, like orientation, is unsuited for common classification methods. Therefore, we split orientation into two more suitable components. Experiments show that the isophote features result in better detection performance than intensities, gradients or Haar-like features.