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An Introduction to Random Forests for Multi-class Object Detection

Juergen Gall, Nima Razavi, Luc van Gool
Outdoor and Large-Scale Real-World Scene Analysis
, Ed.
2012, in press


Object detection in large-scale real world scenes requires efficient multi-class detection approaches. Random forests have been shown to handle large training datasets and many classes for object detection efficiently. The most prominent example is the commercial application of random forests for gaming. In this chapter, we describe the general framework of random forests for multi-class object detection in images and give an overview of recent developments and implementation details that are relevant for practitioners.

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  title = {An Introduction to Random Forests for Multi-class Object Detection},
  booktitle = {Outdoor and Large-Scale Real-World Scene Analysis},
  pages = {},
  year = {2012},
  publisher = {},
  keywords = {},
  note = {in press}