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

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.