Face landmarking, defined as the detection of fiducial points on faces, has received a lot of attention over the last two decades within the computer vision community. While research literature documents major advances using state-of-art deep convolutional neural networks, earlier cascaded regression tree-based approaches remain a relevant alternative for low-cost, low-power embedded systems. Yet, from a practical point of view, their implementation and parametrization can be a difficult and tedious process. In this paper, we provide the readers with insights and advice on how to design a successful face landmarking system using a cascade of regression trees.

在过去的二十年里，计算机视觉界已经引起了很多人的关注，人脸标志是指检测到脸上的基准点。尽管研究文献记录了使用最新的深度卷积神经网络取得的重大进展，但较早的基于级联回归树的方法仍然是低成本，低功耗嵌入式系统的一种相关选择。但是，从实际的角度来看，它们的实现和参数化可能是一个困难而乏味的过程。在本文中，我们为读者提供了有关如何使用级联的回归树设计成功的人脸标记系统的见识和建议。