Director of Research (if dissertation) or Advisor (if thesis)
Do, Minh N.
Doctoral Committee Chair(s)
Do, Minh N.
Committee Member(s)
Patel, Sanjay J.
Hart, John C.
Hoiem, Derek
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Vision
3D
Face Detection
Face Verification
Face Recognition
Head Pose Estimation
Depth Cameras
Abstract
We present a method for real-time 3D face localization and verification using a consumer-grade depth camera. Our approach consists of three parts: face detection, head pose estimation, and face verification. Face detection is performed using a standard detection framework which we significantly improve by leveraging depth information. To estimate the pose of the detected face, we developed a technique that uses a combination of the particle swarm optimization (PSO) and the iterative closest point (ICP) algorithm to accurately align a 3D face model to the measured depth data. With the face localized within the image, we can compare a database 3D face model to the depth image to verify the identity of the subject. We learn a similarity metric using a random decision forest to accurately authenticate the subject. We demonstrate state-of-the-art results for both face localization and face verification on standard datasets. Since the camera and our method operate at video rate, our system is capable of continuously authenticating a subject while he/she uses his/her device.
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