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Viola Jones Object Detection

version 1.1.0.0 (224 KB) by Dirk-Jan Kroon
Viola Jones Object detection using OpenCV trained classifiers

24K Downloads

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 opencv.willowgarage.com


Objects=ObjectDetection(I,FilenameHaarcasade,Options)

inputs,
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

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

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 (https://www.mathworks.com/matlabcentral/fileexchange/29437-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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