Author : Margono, Arie; Gunawan, Ibnu; Lim, Resmana;

Tracking and recognizing human face becomes one of the important research subjects nowadays, where it is applicable in security system like room access, surveillance, as well as searching for person identity in police database. Because of applying in security case, it is necessary to have robust system for certain conditions such as: background influence, non-frontal face pose of male or female in different age and race. The aim of this research is to develop software which combines human face tracking using CamShift algorithm and face recognition system using Embedded Hidden Markov Models. The software uses video camera (webcam) for real-time input, video AVI for dynamic input, and image file for static input. The software uses Object Oriented Programming (OOP) coding style with C++ programming language, Microsoft Visual C++ 6.0® compiler, and assisted by some libraries of Intel Image Processing Library (IPL) and Intel Open Source Computer Vision (OpenCV). System testing shows that object tracking based on skin complexion using CamShift algorithm comes out well, for tracking of single or even two face objects at once. Human face recognition system using Embedded Hidden Markov Models method has reach accuracy percentage of 82.76%, using 341 human faces in database that consists of 31 individuals with 11 poses and 29 human face testers.

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