Proc. SPIE. 8288, Stereoscopic Displays and Applications XXIII
KEYWORDS: Video, Video coding, Cameras, Neodymium, 3D video compression, Video compression, Stereoscopic cameras, Photonic integrated circuits, Surface conduction electron emitter displays, Electronics
One of the important issues for a next generation broadcasting system is how to compress a massive amount of threedimensional
(3D) video efficiently. In this paper, we propose a geometry compensation method for 3D video coding
exploiting color videos, depth videos and camera parameters. In the proposed method, we first generate a compensated
view, which is located at the geometrically same position with the current view, using depth and camera parameters of
neighboring views. Then, the compensated view is used as a reference picture to reduce the inter-view redundancies such
as disparity and motion vectors. Furthermore, considering the direction of hole-regions, we propose a hole-filling method
for picture of P-view to fill up the holes based on the neighboring background pixels. The experimental results show that
the proposed algorithm increases BD-PSNRs up to 0.22dB and 0.63dB for P- and B-views, respectively. Meanwhile, we
achieved up to 6.28% and 18.32% BD bit-rates gain for P- and B- views, respectively.
The inter-view prediction is used as well as the temporal prediction in order to exploit both the temporal and inter-view
redundancies in multiview video coding. Accordingly, the multiview video coding has two types of motion vectors that
are the temporal motion vector and the disparity vector, respectively. The disparity vector is generally uncorrelated with
the temporal motion vector. However, they are used together to predict the motion vector regardless of their types,
therefore an efficiency of the conventional predictive coding of multiview video coding is decreased. In order to increase
the accuracy of the predicted motion vector, a new motion vector prediction method including virtual temporal motion
vector and virtual disparity vector is proposed for both the multiview video and multiview video plus depth formats. The
experimental results show that the proposed method can reduce the coding bitrates by 6.5% in average and 14.6% at
maximum in terms of Bjontegaard metric compared to the conventional method.
Multi-view video coding (MVC) is a video coding standard developed by MPEG and VCEG for multi-view video. It
showed average PSNR gain of 1.5dB compared with view-independent coding by H.264/AVC. However, because
resolutions of multi-view video are getting higher for more realistic 3D effect, high performance video codec is needed.
MVC adopted hierarchical B-picture structure and inter-view prediction as core techniques. The hierarchical B-picture
structure removes the temporal redundancy, and the inter-view prediction reduces the inter-view redundancy by
compensated prediction from the reconstructed neighboring views. Nevertheless, MVC has inherent limitation in coding
efficiency, because it is based on H.264/AVC. To overcome the limit, an enhanced video codec for multi-view video
based on Key Technology Area (KTA) is proposed. KTA is a high efficiency video codec by Video Coding Expert
Group (VCEG), and it was carried out for coding efficiency beyond H.264/AVC. The KTA software showed better
coding gain than H.264/AVC by using additional coding techniques. The techniques and the inter-view prediction are
implemented into the proposed codec, which showed high coding gain compared with the view-independent coding
result by KTA. The results presents that the inter-view prediction can achieve higher efficiency in a multi-view video
codec based on a high performance video codec such as HEVC.
Stereoscopic video delivers depth perception to users contrary to 2-dimenstional video. Therefore, we need to develop a
new video quality assessment model for stereoscopic video. In this paper, we propose a new method for objective
assessment of stereoscopic video. The proposed method detects blocking artifacts and degradation in edge regions such
as in conventional video quality assessment model. In addition, it detects video quality difference between views using
depth information. We performed subjective evaluation of stereoscopic video to verify the performance of the proposed
method, and we confirmed that the proposed algorithm is superior to PSNR in respect to correlation with the subjective
View synthesis technique is essential for FTV (Free viewpoint TV) systems. In this paper, we propose a multi-step view
synthesis algorithm to efficiently reconstruct an arbitrary view from limited number of known views of a 3D scene. We
describe an efficient image rectification procedure which guarantees that an interpolation process produces valid views.
This rectification method can be extended to multi-view images. Since, it transforms only one image. Then, to generate
high quality intermediate views, we use an efficient dense disparity estimation algorithm with occlusion handling. Main
concept of the algorithm is based on the region dividing bidirectional pixel matching. Estimated disparity vectors are
used to synthesize intermediate view of stereo images with occlusion handling. Experimental results show that the
performance is superior to other approaches.
In general, it is necessary for Multi-view Video Coding (MVC) methods to compress multi-view videos efficiently and
have a property of view-scalability in order to decode arbitrary views according to any viewer's interests. Much research
has been done on MVC methods, with the goal of increasing coding efficiency. Although these previous methods have
considered the property of view-scalability, a lot of coding bits and delays were necessary to decode arbitrary views. In
this paper, we propose an MVC method based on image stitching. We generated a stitched reference and encoded multiview
sequences using disparity-compensated method. The proposed method is able to reduce delays during the decoding
stage. Experimental results show that the proposed MVC method increased the PSNR by 1.5~2.0dB and saved 10% of
the coding bits compared to simulcast coding.