This book presents the thoroughly revised versions of lectures given by leading researchers during the Workshop on Advanced 3D Imaging for Safety and Security in conjunction with the International Conference on Computer Vision and Pattern Recognition CVPR 2005, held in San Diego, CA, USA in June 2005. It covers the current state of the art in 3D imaging for safety and security.

Zusammenfassung
The past decades have seen significant improvements in 3D imaging where the related techniques and technologies have advanced to a mature state. These exciting developments have sparked increasing interest in industry and academia in the challenges and opportunities afforded by 3D sensing. As a consequence, the emerging area of safety and security related imaging incorporates these important new technologies beyond the limitations of 2D image processing. This book is so far the first that covers the current state of the art in 3D imaging for safety and security. It reports about selected contributions given at the Workshop on Advanced 3D Imaging for Safety and Security held in conjunction with the International Conference on Computer Vision and Pattern Recognition CVPR 2005, June 2005, San Diego, CA. The workshop brought together pioneering academic and industrial researchers in the field of computer vision and image analysis. Special attention was given to advanced 3D imaging technologies in the context of safety and security applications. Comparative evaluation studies showing advantages of 3D imaging over traditional 2D imaging for a given computer vision or pattern recognition task were emphasized. Moreover, additional experts in the field of 3D imaging for safety and security were invited by the editors for a contribution to this book. The book is structured into two parts, each containing five or six chapters on (1) Biometrics and (2) Safety and Security Applications.

Leseprobe

Chapter 2 A SURVEY ON 3D MODELING OF HUMAN FACES FOR FACE RECOGNITION (P. 25)

*S. Huq, B. Abidi, S. G. Kong, and M. Abidi
Imaging, Robotics, and Intelligent Systems, The University of Tennessee, Knoxville,
TN 37996-2100, USA.*
Abstract:

In its quest for more reliability and higher recognition rates the face recognition community has been focusing more and more on 3D based recognition. Depth information adds another dimension to facial features and provides ways to minimize the effects of pose and illumination variations for achieving greater recognition accuracy. This chapter reviews, therefore, the major techniques for 3D face modeling, the first step in any 3D assisted face recognition system.

The reviewed techniques are laser range scans, 3D from structured light projection, stereo vision, morphing, shape from motion, shape from space carving, and shape from shading. Concepts, accuracy, feasibility, and limitations of these techniques and their effectiveness for 3D face recognition are discussed.

Key words:

3D face reconstruction, face recognition, laser range scanner, structured light, stereo vision, morphing, shape from shading, shape from motion.

1. INTRODUCTION

Biometrics-based techniques such as fingerprint and iris matching often require physical contact or cooperation of the user. Face recognition offers a reliable means for personal identification without requiring much of the participant s cooperation.

Despite the success in various applications, recognizing human faces in an uncontrolled environment has remained largely unsolved. The appearance of a face, an inherently three-dimensional (3D) object, projected onto a two-dimensional Face recognition has become one of the most active research fields in (2D) space is sensitive to the variations in pose and illumination.

Even, face variations of the same person created by pose and illumination changes could become larger than variations between individuals1. Face recognition techniques assisted with 3D facial models promise to overcome the difficulties and limitations associated with face recognition in 2D space.

In addition to being an important additional feature in recognition, depth plays a crucial role in mitigating variations caused by pose and illumination. In the acquisition of facial images using cameras deployed for surveillance or access control, people move freely with their faces appearing at any angle.

In this case, a smart face recognition system should be able to reproduce the same 2D rendering of the face as in the database for an accurate comparison. Once modeled in 3D, faces can accurately be back projected at any angle for matching.

The major goal of this chapter is to present a comprehensive review of the current technologies for modeling 3D human faces. Several related topics such as (1) the use of 3D face images in face recognition, (2) existing 3D face databases (publicly available), and (3) future trends of 3D face modeling and recognition have also been covered.

3D face modeling techniques can be divided into two classes - active and passive - depending on the imaging modalities and reconstruction methods.

Inhalt
Biometrics.- 3D Assisted Face Recognition: A Survey.- A Survey on 3D Modeling of Human Faces for Face Recognition.- Automatic 3D Face Registration Without Initialization.- A Genetic Algorithm Based Approach for 3D Face Recognition.- Story of Cinderella.- Human Ear Detection From 3D Side Face Range Images.- Safety and Security Applications.- Synthetic Aperture Focusing Using Dense Camera Arrays.- Dynamic Pushbroom Stereo Vision.- 3D Modeling of Indoor Environments.- 3D Site Modelling and Verification.- Under Vehicle Inspection with 3d Imaging.