# Object Detection with Pixel Intensity Comparisons Organized in Decision Trees

Source: [Object Detection with Pixel Intensity Comparisons Organized in Decision Trees](<https://www.sota2.com/research/paper/68fa617a1e209131ce9f4494>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T19:59:37.091Z

Authors: Nenad Marku\\v{s}, Miroslav Frljak, Igor S. Pand\\v{z}i\\'c, J\\"orgen Ahlberg, Robert Forchheimer

Published: 2013-05-20T14:35:47.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1305.4537>)

[PDF](<https://arxiv.org/pdf/1305.4537.pdf>)