On face detection in the compressed domain

ABSTRACT

We propose a fast face detection algorithm that works directly on the compressed DCT domain. Unlike the previous DCT domain processing designs that are mainly based on skin-color detection, our algorithm analyzes both color and texture information contained in the DCT parameters, therefore could generate more reliable detection results. Our texture analysis is mainly based on statistical model training and detection. A number of fundamental problems, e.g., block quantization, preprocessing in the DCT domain, and feature vector selection and classification in the DCT domain, are discussed.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Feature evaluation and selection

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Texture
  I.4 IMAGE PROCESSING AND COMPUTER VISION
      I.4.1 Digitization and Image Capture
          Subjects: Quantization
      I.4.7 Feature Measurement
          Subjects: Texture
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Classifier design and evaluation

General Terms:
Algorithms, Design, Experimentation, Human Factors, Management, Measurement, Performance, Theory

Keywords:
DCT, JPEG, MPEG, face detection