Director of Research (if dissertation) or Advisor (if thesis)
Do, Minh N.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
3D Modeling
3D Camera
Surface Reconstruction
Face Detection
Kinect
Abstract
Modeling the 3D geometry of the face is an important research topic in computer
graphics and computer vision.
The applications for face models include computer animation and facial analysis.
Over the past few decades, several face modeling techniques have been developed
using both active and passive sensors.
Unlike passive sensors, which reconstruct the geometry of the face using
reflected ambient light, active sensors measure the geometry of the face by
emitting an external light source onto the surface of the face.
As a result, techniques that utilize active sensors often produce higher quality
face models, but the active sensors are typically expensive.
Recently, low-cost consumer depth cameras have become widely available due to
the success of Microsoft's Kinect camera.
The Kinect is an active sensor that provides depth images at video rate;
however, the images are often noisy and missing measurements.
In this thesis, we present a method for modeling the geometry of the face using
a consumer depth camera.
To construct a high quality model, we combine the surface measurements from
multiple depth images.
By registering and integrating a sequence of depth images, we are
able to recover the entire surface of the face and reduce noise.
We demonstrate that 3D face models built using our proposed method are
comparable to models generated using an expensive, high-resolution 3D scanner.
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