A support vector machine approach for real time vision based human robot interaction

Abstract

Today humanoid robots are being exhibited to redact various task as a personal assistant of a human. To be an assistant, a robot needs to interact with human as a human. For this reason robot needs to understand the human gender, facial expression, facial gesture in real time. Ribo — A humanoid robot build in RoboSUST lab which has the ability to communicate in Bangla with the people speaking in Bengali. In this article the authors show the implementation of theoretical knowledge of the recognition of real time facial expression, detection of human gender and yes / no from facial gesture in Ribo. Real time facial expression and gender detection can be performed using Support Vector Machine (SVM). A prepared dataset containing the facial landmarks leveled as five different expression: sad, angry, smile, surprise and normal, is given to SVM to construct a classifier. For the prediction of any expression, facial images are taken in real time and provided the facial landmarks data to SVM. Local Binary Pattern(LBP) algorithm is used for extracting features from face images. These features leveled as male and female are responsible to build the classifier. The face gesture for detecting ‘yes/no’ is performed by tracking the movement of face in a certain time. After those implementations the principal results will make a framework that will be used in Ribo to recognize human facial expression, facial gesture movement and detect human gender.