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Three-dimensional sensor-based face recognition.

Hwanjong Song1, Sangyoun Lee, Jaihie Kim

  • 1Department of Electrical and Electronic Engineering, Biometrics Engineering Research Center, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, South Korea. ultrarex@diml.yonsei.ac.kr

Applied Optics
|March 9, 2005
PubMed
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This study introduces a novel 3D face recognition system using structured-light and laser scanning. The system effectively overcomes pose variation challenges, achieving promising face recognition rates.

Area of Science:

  • Computer Science
  • Biometrics
  • Image Processing

Background:

  • Two-dimensional (2D) face recognition struggles with pose variations.
  • Three-dimensional (3D) sensing offers a potential solution to these limitations.
  • Existing 3D face recognition methods may have limitations in data acquisition or processing.

Purpose of the Study:

  • To develop and evaluate a novel 3D face recognition system.
  • To address the challenge of pose variation in face recognition.
  • To compare data acquired from structured-light and laser scanning systems.

Main Methods:

  • Utilized two distinct 3D sensors: a structured-light system for input data and a 3D laser scanner for reference data.
  • Generated range images from both sensor types to handle structural differences.

Related Experiment Videos

  • Proposed an error-compensated singular-value decomposition for accurate head pose estimation.
  • Applied principal component analysis (PCA) for face recognition on range images.

    • Main Results:

    • Demonstrated the system's capability to overcome pose-variation problems inherent in 2D methods.
    • Achieved promising face recognition rates on a dataset of 35 individuals.
    • Successfully estimated head pose using the novel error-compensated SVD method.

    Conclusions:

    • The developed 3D face recognition system shows significant potential for robust identification.
    • The combination of 3D sensing technologies and advanced algorithms effectively handles pose variations.
    • Further research can build upon these findings for enhanced biometric security solutions.