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2 Machine Graphics and Vision

2 2007

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Mathematical morphology based automated control point detection from human facial image

Haider M. A., Rahman I. S., Islam M., Shahiduzzaman M.

Machine Graphics and Vision

2007

Vol. 16, No. 1/2

153-170

The ultimate goal of this research is to incorporate facial animation based on image morphing in a very narrow bandwidth video transmission, especially in video conferencing, news telecast etc., where the background as well as the object in the image change little. As a part of the whole work, in this paper, an efficient mathematical morphology-based facial feature control point detection technique is proposed. By facial feature control point we mean facial feature (i.e. eye, lip etc.) surrounding points and other important points in the face which can be utilized to create facial animation based on image metamorphosis. In the experiment, mathematical morphology tools are used both for filtering and pattern matching. At first, intensity-independent, color-based segmentation is used with some morphological processing on the input image to separate skin regions. Then, the parallel eye segments are searched by erosion of the edge-thinned image with eye corner structuring elements. By combining them, the probable eye segment pair is identified. Then, using facial structural knowledge, the lips and other control points are detected. The accuracy of the proposed method is within quite acceptable limits; moreover, the method is capable of working with images of average quality or close to average quality.

An efficient facial expression detection system

Tumpi P. N., Rahman W. R., Haider M. A.

Machine Graphics and Vision

2007

Vol. 16, No. 3/4

377-399

In this paper we present an effective and robust approach for detecting a Bangladeshi facial expression in a 2D image. The facial expression is one of the most powerful, natural and immediate means for human beings to communicate their emotions and intentions. Most of the existing works on expression analysis have been focused on the facial expressions of European and American people, but these basic expressions vary subtly with races all over the world. We have tried to explore this diversity and to automate the facial expression detection for people of the Indian sub-continent, especially Bangladeshi people. Consequently, we have recommended a modified set of AUs (Action Units) defined in the FACS (the Facial Action Coding System), which is the leading standard for measuring facial expressions in the behavioral sciences. In this work, we propose a method to combine feature detection and extraction and facial expression detection into an integrated system. The main aspect of our system is that it covers all the criteria essential for detecting the facial expression of the people inhabiting sub-continent especially Bangladeshi people. Though the system concentrates on a particular race, it is also successful to a great extent with other races in the world, which proves its flexibility and robustness.