  The compression quality losses of depth sequences determine quality of view
synthesis in free-viewpoint video. The depth map intra prediction in 3D
extensions of the HEVC applies intra modes with auxiliary depth modeling modes
(DMMs) to better preserve depth edges and handle motion discontinuities.
Although such modes enable high efficiency compression, but at the cost of very
high encoding complexity. Skipping conventional intra coding modes and DMMs in
depth coding limits practical applicability of the HEVC for 3D display
applications. In this paper, we introduce a novel low-complexity scheme for
depth video compression based on low-rank tensor decomposition and HEVC intra
coding. The proposed scheme leverages spatial and temporal redundancy by
compactly representing the depth sequence as a high-order tensor. Tensor
factorization into a set of factor matrices following CANDECOMP PARAFAC (CP)
decomposition via alternating least squares give a low-rank approximation of
the scene geometry. Further, compression of factor matrices with HEVC intra
prediction support arbitrary target accuracy by flexible adjustment of bitrate,
varying tensor decomposition ranks and quantization parameters. The results
demonstrate proposed approach achieves significant rate gains by efficiently
compressing depth planes in low-rank approximated representation. The proposed
algorithm is applied to encode depth maps of benchmark Ballet and Breakdancing
sequences. The decoded depth sequences are used for view synthesis in a
multi-view video system, maintaining appropriate rendering quality.
