The advances in display technologies and the
growing popularity of 3D video systems have attracted
more consumers for 3D viewing experiences, and, conse-
quently, the demand for storage and transmission of 3D
video content is increasing. To cope with this demand, a
3D video extension of high-efficiency video coding
(HEVC) standard is being developed and near the final
standardization stage. The upcoming 3D-HEVC standard is
expected to provide higher encoding efficiency than its
predecessors, supporting multiple views with high resolu-
tion, at a cost of considerable increase in computational
complexity, which can be an obstacle to its use in real-time
applications. This article proposes a novel complexity
reduction algorithm developed to optimize the 3D-HEVC
intra mode decision targeting real-time video processing
for consumer devices with limited computational power,
such as 3D camcorders and smartphones equipped with
multiple cameras and depth acquisition capabilities. The
proposed algorithm analyzes the texture frames and depth
maps to estimate the orientation of edges present in the
prediction unit data, speeding up the intra prediction pro-
cess and reducing the 3D-HEVC encoding processing time.
Experimental results demonstrate that the proposed algo-
rithm can save 26 % in computational complexity on
average with negligible loss of encoding efficiency. This
solution contributes to make more feasible the compression
of 3D videos targeting real-time applications in power-
constrained devices.