Jianglong Chang

  • Citations Per Year
Learn More
Since the human faces are lowly textured, the conventional stereo methods based on intensity correlation can not give satisfying 3D face reconstruction results. In this paper, a model based stereo matching method is proposed. A reference 3D face is used as an intermedium for correspondence calculation. The virtual face images with known correspondences are(More)
This paper proposes a method for acquiring face depth information directly from near infrared (NIR) images, using statistical learning. To perform such learning, ground truth NIR images and range data are captured. A method of alignment between the two image modalities is proposed. By constructing the low dimensional face subspaces of NIR images and depth(More)
This paper introduces a bilinear model to analyze and transfer expression or identity of 3D faces, and its applications in 3D and 2D areas. Our aim is to separate identity and expression factors of face data into two independent linear subspaces. First all the data are proceeded to have vertex-to-vertex correspondences. We build a morphable face model to(More)
This paper presents a method that can directly establish dense correspondences between 3D faces with arbitrary expressions and identities. We propose a re-sampling algorithm which uses a reference 3D face to re-sample target 3D faces under the guidance of radial basis function (RBF) network. The algorithm not only establishes dense correspondences between(More)
  • 1