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Viola Jones Object Detection

version (224 KB) by Dirk-Jan Kroon
Viola Jones Object detection using OpenCV trained classifiers


Updated 18 Nov 2010

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This function ObjectDetection is an implementation of the Detection in the Viola-Jones framework. In this framework Haar-like features are used for rapid object detection. It supports the trained classifiers in the XML files of OpenCV which can be download as part of the OPENCV software on


I : 2D image, or Filename of an image
FilenameHaarcasade : The filename of a Matlab file with a Haarcasade which is created from an OpenCV xml file
Options : A struct with options
Options.ScaleUpdate : The scale update, default 1/1.2
Options.Resize : If boolean is true (default), the function will
resize the image to maximum size 384 for less cpu-time
Options.Verbose : Display process information

Objects : An array n x 4 with [x y width height] of the detected

Literature :
- Rainer Linehart and Jochend Maydt, "An Extended Set of Haar-like
Features for Rapid Object Detection"
- Paul viola and Michael J. Jones, "Rapid Object Detection using
a Boosted Cascade of Simple Features", 2001

Example 1,
% % Convert an OpenCV classifier XML file to a Matlab file
% ConvertHaarcasadeXMLOpenCV('HaarCascades/haarcascade_frontalface_alt.xml');
% % Detect Faces
% Options.Resize=false;
% ObjectDetection('Images/1.jpg','HaarCascades/haarcascade_frontalface_alt.mat',Options);

Cite As

Dirk-Jan Kroon (2022). Viola Jones Object Detection (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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