Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
Computer Vision and Pattern Recognition
2014-08-20 v5
Abstract
We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors. The trees use pixel intensity comparisons in their internal nodes and this makes them able to process image regions very fast. Experimental analysis is provided through a face detection problem. The obtained results are encouraging and demonstrate that the method has practical value. Additionally, we analyse its sensitivity to noise and show how to perform fast rotation invariant object detection. Complete source code is provided at https://github.com/nenadmarkus/pico.
Cite
@article{arxiv.1305.4537,
title = {Object Detection with Pixel Intensity Comparisons Organized in Decision Trees},
author = {Nenad Markuš and Miroslav Frljak and Igor S. Pandžić and Jörgen Ahlberg and Robert Forchheimer},
journal= {arXiv preprint arXiv:1305.4537},
year = {2014}
}