Detection and Tracking of Facial Features by Using Edge Pixel Counting and Deformable Circular Template Matching

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In this paper face feature detection and tracking are discussed, using methods called edge pixel counting and deformable circular template matching. Instead of utilizing color or gray scale information of the facial image, the proposed edge pixel counting method utilizes the edge information to estimate the face feature positions such as eyes, nose and mouth, using a variable size face feature template, the initial size of which is predetermined by using a facial image database. The method is robust in the sense that the detection is possible with facial images with different skin color and different facial orientations. Subsequently, by using a deformable circular template matching two iris positions of the face are determined and are used in the edge pixel counting, to track the features in the next frame. Although feature tracking using gray scale template matching often fails when inter frame correlation around the feature areas are very low due to facial expression change (such as, talking, smiling, eye blinking etc.), feature tracking using edge pixel counting can track facial features reliably. Some experimental results are shown to demonstrate the effectiveness of the proposed method.

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詳細情報

  • CRID
    1572543027349304704
  • NII論文ID
    110003219734
  • NII書誌ID
    AA10826272
  • ISSN
    09168532
  • 本文言語コード
    en
  • データソース種別
    • CiNii Articles

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