Talks and Poster Presentations (with Proceedings-Entry):

J. Cho, S. Ikehata, H. Yoo, M. Gelautz, K. Aizawa:
"Depth Map Upsampling using Cost-Volume Filtering";
Talk: 11th IEEE IVMSP Workshop, Korea; 2013-06-10 - 2013-06-12; in: "Proc. of IVMSP Workshop", (2013), 1 - 4.

English abstract:
Depth maps captured by active sensors (e.g., ToF cameras and Kinect) typically suffer from poor spatial resolution, considerable amount of noise, and missing data. To overcome these problems, we propose a novel depth map up-sampling method which increases the resolution of the original depth map while effectively suppressing aliasing artifacts. Assuming that a registered high-resolution texture image is available, the cost-volume filtering framework is applied to this problem. Our experiments show that cost-volume filtering can generate the high-resolution depth map accurately and efficiently while preserving discontinuous object boundaries, which is often a challenge when various state-of-the-art algorithms are applied.

Depth map super-resolution, cost-volume filtering, up-sampling

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Related Projects:
Project Head Margrit Gelautz:
3D VideoFusion

Created from the Publication Database of the Vienna University of Technology.