Interactive free-viewpoint selection applied to a 3D multi-view video signal is an attractive feature of the rapidly
developing 3DTV media. In recent years, significant research has been done on free-viewpoint rendering algorithms
which mostly have similar building blocks. In our previous work, we have analyzed the principal
building blocks of most recent rendering algorithms and their contribution to the overall rendering quality. We
have discovered that the first step, Warping determines the basic quality level of the complete rendering chain.
In this paper, we have analyzed the warping step in more detail since it leads to ways for improvement. We have
observed that the accuracy of warping is mainly determined by two factors which are sampling and rounding
errors when performing pixel-based warping and quantization errors of depth maps. For each error factor, we
have proposed a technique that can reduce the errors and thus increase the warping quality. Pixel-based warping
errors are reduced by employing supersampling at the reference and virtual images and we decrease depth map
errors by creating depth maps with more quantization levels. The new techniques are evaluated with two series of
experiments using real-life and synthetic data. From these experiments, we have observed that reducing warping
errors may increases the overall rendering quality and that the impact of errors due to pixel-based warping is
much larger than that of errors due to depth quantization.
KEYWORDS: Video, 3D video streaming, Cameras, Internet, Video compression, Computer programming, 3D video compression, Video coding, Quantization, Receivers
Virtual views in 3D-TV and multi-view video systems are reconstructed images of the scene generated synthetically
from the original views. In this paper, we analyze the performance of streaming virtual views over
IP-networks with a limited and time-varying available bandwidth. We show that the average video quality
perceived by the user can be improved with an adaptive streaming strategy aiming at maximizing the average
video quality. Our adaptive 3D multi-view streaming can provide a quality improvement of 2 dB on the average
- over non-adaptive streaming. We demonstrate that an optimized virtual view adaptation algorithm needs to
be view-dependent and achieve an improvement of up to 0.7 dB. We analyze our adaptation strategies under
dynamic available bandwidth in the network.
KEYWORDS: Cameras, Video, Volume rendering, Digital filtering, Video compression, Optical filters, Image quality, Algorithm development, 3D image processing, 3D modeling
Interactive free-viewpoint selection applied to a 3D multi-view signal is a possible attractive feature of the
rapidly developing 3D TV media. This paper explores a new rendering algorithm that computes a free-viewpoint
based on depth image warping between two reference views from existing cameras. We have developed three
quality enhancing techniques that specifically aim at solving the major artifacts. First, resampling artifacts are
filled in by a combination of median filtering and inverse warping. Second, contour artifacts are processed while
omitting warping of edges at high discontinuities. Third, we employ a depth signal for more accurate disocclusion
inpainting. We obtain an average PSNR gain of 3 dB and 4.5 dB for the 'Breakdancers' and 'Ballet' sequences,
respectively, compared to recently published results. While experimenting with synthetic data, we observe that
the rendering quality is highly dependent on the complexity of the scene. Moreover, experiments are performed
using compressed video from surrounding cameras. The overall system quality is dominated by the rendering
quality and not by coding.
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