Activity 1. Adaptive Segmentation and Tracking Using the Color Locus

Introduction

In this activity, an adaptive histogram backprojection method is utilized to track the face of the subject in a video clip, under varying illumination. This is done by creating a color locus first.

The color locus is estimated using the rg-histograms of selected pre-cropped pictures of the subject's skin under varrying illumination. The video is then parsed into image frames, where a frame-by-frame histogram backprojection is done. This histogram is adapted based on the object locus.

Before doing this, I reviewed the concept of histogram back-projection using Scilab (I hope to put up my blog for this topic later). Then I used VirtualDub for parsing the video of Kirby and then I moved to Matlab for the rest of this activity.


Results
The processing of the subject's video is now done using Matlab. A successful implemetation as seen below is an unbroken tracking of the subject's face under varying illumination.

Figure 1. Tracking the face of the subject.

Successful tracking of the subject's face was obtained even when the subject was under varrying illumination as seen in the above figure.

For this activity, I give myself a grade of 10 for I could track the face of Kirby (the subject ^^) under different illumination and I exerted a lot of effort from reviewing in Scilab to finally implementing it in Matlab.

Thanks to the graduating batch for teaching me especially when I was reviewing histogram backprojection in Scilab. ^^

Reference:
1. Physics 305 handouts by M. Soriano
2. Soriano, Martinkauppi, Huovinen, Laaksonen, Adaptive skin color modeling modeling using the skin locus for selecting training pixels, Pattern Recognition, Vol. 36, No. 3, March 2003