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Depth Map Compression Using Color-Driven Isotropic Segmentation and Regularised Reconstruction

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoData Compression Conference Proceedings
KustantajaThe Institute of Electrical and Electronics Engineers, Inc.
Sivut153-162
Sivumäärä10
Vuosikerta2015-July
ISBN (painettu)9781479984305
DOI - pysyväislinkit
TilaJulkaistu - 2 heinäkuuta 2015
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaDATA COMPRESSION CONFERENCE -
Kesto: 1 tammikuuta 1900 → …

Conference

ConferenceDATA COMPRESSION CONFERENCE
Ajanjakso1/01/00 → …

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.

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