3D Face Modeling for Multi-Feature Extraction for Intelligent Systems

3D Face Modeling for Multi-Feature Extraction for Intelligent Systems

Zahid Riaz (Technische Universität München, Germany), Suat Gedikli (Technische Universität München, Germany), Michael Beetz (Technische Universität München, Germany) and Bernd Radig (Technische Universität München, Germany)
Copyright: © 2011 |Pages: 17
DOI: 10.4018/978-1-60960-024-2.ch005
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Abstract

In this chapter, we focus on the human robot joint interaction application where robots can extract the useful multiple features from human faces. The idea follows daily life scenarios where humans rely mostly on face to face interaction and interpret gender, identity, facial behavior and age of the other persons at a very first glance. We term this problem as face-at-a-glance problem. The proposed solution to this problem is the development of a 3D photorealistic face model in real time for human facial analysis. We also discuss briefly some outstanding challenges like head poses, facial expressions and illuminations for image synthesis. Due to the diversity of the application domain and optimization of relevant information extraction for computer vision applications, we propose to solve this problem using an interdisciplinary 3D face model. The model is built using computer vision and computer graphics tools with image processing techniques. In order to trade off between accuracy and efficiency, we choose wireframe model which provides automatic face generation in real time. The goal of this chapter is to provide a standalone and comprehensive framework to extract useful multi-feature from a 3D model. Such features due to their wide range of information and less computational power, finds their applications in several advanced camera mounted technical systems. Although this chapter focuses on multi-feature extraction approach for human faces in interactive applications with intelligent systems, however the scope of this chapter is equally useful for researchers and industrial practitioner working in the modeling of 3D deformable objects. The chapter mainly specified to human faces but can also be applied to other applications like medical imaging, industrial robot manipulation and action recognition.
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Background

In the recent decade advancement in the field of camera technology, their mountability on mobiles and availability of high computational powers in personal computers have increased the demand of the user to extract more information from the images for higher applications. For instance, face detection cameras, smile-capture cameras and face recognition in notebooks. Future systems will be relying more on the facial image analysis, especially socially inspired robots need to know about the behavior of interacting person at a very first glance. In this manner robots can get friendly with the humans in the very first meeting and can adapt themselves easily to the interacting person’s habits. The applications of such system can further be extended to intelligent nurses for patients and assistive robots for elders.

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