@inproceedings{24e6ed18f0be40ccbf56a76b29882b52,
title = "Camera pose estimation for mixed and diminished reality in FTV",
abstract = "In this paper, we will present methods for camera pose estimation for mixed and diminished reality visualization in FTV application. We first present Viewpoint Generative Learning (VGL) based on 3D scene model reconstructed using multiple cameras including RGB-D camera. In VGL, a database of feature descriptors is generated for the 3D scene model to make the pose estimation robust to viewpoint change. Then we introduce an application of VGL to diminished reality. We also present our novel line feature descriptor, LEHF, which is also be applied to a line-based SLAM and improving camera pose estimation.",
keywords = "augmented reality, camera calibration, feature descriptor, free viewpoint image synthesis, see-through vision",
author = "Hideo Saito and Toshihiro Honda and Yusuke Nakayama and {De Sorbier}, Francois",
year = "2014",
doi = "10.1109/3DTV.2014.6874756",
language = "English",
isbn = "9781479947584",
series = "3DTV-Conference",
publisher = "IEEE Computer Society",
booktitle = "3DTV-Conference",
note = "3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video, 3DTV-CON 2014 ; Conference date: 02-07-2014 Through 04-07-2014",
}