Depth Map Compression Using Color-Driven Isotropic Segmentation and Regularised Reconstruction
Georgiev, Mihail; Belyaev, Evgeny; Gotchev, Atanas (2015-07-02)
Georgiev, Mihail
Belyaev, Evgeny
Gotchev, Atanas
The Institute of Electrical and Electronics Engineers, Inc.
02.07.2015
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201606064217
https://urn.fi/URN:NBN:fi:tty-201606064217
Kuvaus
Peer reviewed
Tiivistelmä
'View-plus-depth' is a popular 3D image representation format, in which the color 2D image is augmented with a gray-scale image representing the scene depth map aligned with the color pixels. In this paper, we propose a novel depth map compression method aimed at finding an optimal spatial depth scale and down-sampling (sparsifying) the depth image over it. The down-sampled depth image is then compressed by a combination of a new arithmetic and a predictive coder. Our approach is motivated by the current achievements in multi-sensor 3D scene sensing where low-resolution depth map captured by time-of-flight sensors is successfully up-sampled and aligned with high resolution RGB images. In our approach, color image segmentation in terms of super-pixels is used for finding the optimal depth scale and corresponding down-sampling. In contrast to other segmentation methods, it results in an isotropic and balanced low-resolution depth image, which is easily compressible. A bilateral regularizer is used for reconstructing the original-size depth map out of the low-resolution one and for splitting and predictive coding of segments with high reconstruction error. The scheme compares favorably with other methods for depth map compression.
Kokoelmat
- TUNICRIS-julkaisut [16929]