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CASME II: an improved spontaneous micro-expression database and the baseline evaluation.

Wen-Jing Yan1, Xiaobai Li2, Su-Jing Wang3

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Developing a high-quality micro-expression database (CASME II) with improved resolution is crucial for advancing automatic recognition systems. This new dataset enables better training for applications in safety, law enforcement, and healthcare.

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Area of Science:

  • Computer Vision
  • Biometrics
  • Human-Computer Interaction

Background:

  • Automatic micro-expression recognition systems are vital for national safety, police interrogation, and clinical diagnosis.
  • Existing micro-expression databases lack sufficient high-quality training samples.
  • Previous databases have limitations in temporal and spatial resolution.

Purpose of the Study:

  • To address the scarcity of high-quality micro-expression data.
  • To develop an improved micro-expression database (CASME II) with enhanced resolution.
  • To provide a benchmark for evaluating micro-expression recognition algorithms.

Main Methods:

  • A review of existing micro-expression databases was conducted.
  • The CASME II database was created with a temporal resolution of 200 fps and spatial resolution of approximately 280x340 pixels.
  • Facial expressions were elicited under controlled laboratory conditions with proper illumination.
  • 247 micro-expressions were selected from nearly 3000 facial movements and labeled with action units (AUs) and emotions.
  • Baseline evaluation used Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) for feature extraction and Support Vector Machines (SVM) for classification.
  • Leave-one-subject-out cross-validation was employed.

Main Results:

  • The CASME II database contains 247 labeled micro-expressions.
  • Baseline evaluation achieved a best performance of 63.41% for 5-class classification.
  • The database offers higher temporal and spatial resolution compared to previous datasets.

Conclusions:

  • The CASME II database represents a significant improvement for micro-expression research.
  • The enhanced resolution and quality of CASME II facilitate the development of more robust automatic micro-expression recognition systems.
  • Further research can leverage CASME II for developing advanced facial expression analysis tools.