Face Detection

A method for Face Detection that uses a 3D Model to constrain the face keypoint positions.

 Publications:
  • A. Barbu, N. Lay, G.Gramajo. Face Detection with a 3D Model. Academic Press Library in Signal Processing Volume 6: Image and Video Processing and Analysis and Computer Vision. pp 237-259, 2018. Editors: R. Chellappa and S. Theodoridis. (arxiv)
  • A. Barbu. Multi-Path Marginal Space Learning for Object Detection. Academic Press Library in Signal Processing: Volume 4: Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing. pp 271–291, 2013 (pdf)

1 comment:

  1. for.May 8, 2026 at 6:03 PM

    A 3D model–based face detection method uses a predefined 3D face structure to guide and constrain the positions of facial keypoints (landmarks). This approach improves robustness under pose variations, occlusions, and lighting changes compared to purely 2D methods. Keypoint Detection Projects

    Core Idea

    Instead of detecting facial landmarks independently in 2D, the method:

    Uses a 3D face model (generic or statistical)
    Projects it onto the 2D image plane
    Constrains detected keypoints to follow valid 3D facial geometry

    This ensures that the predicted landmarks form a realistic human face shape. Image Processing Projects For Final Year

    ReplyDelete

Subscribe to: Posts (Atom)