Search

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.

In this paper, we proposed a visual fatigue monitoring system based on eye-movement and eye-blink detection. It analyzes the eye-movement and number of blinks based on the assumption that saccade movement of the eye decreases and the number of eye blink increases when visual fatigue of viewer is accumulated. The proposed system has an infrared single camera and an infrared light source. Then, the pupil of the eye can be detected by applying binary threshold to Purkinje image. The threshold is automatically selected by two constraints which are the eccentricity of ellipse fitting and the size of the pupil. Finally, total amount of eye movement and the number of eye blinks are measured by using the positions of the pupil. The results were obtained while watching stereoscopic videos after personal calibration procedure. The results show that saccade movement of the eye decreases as the visual fatigue of the viewer is accumulated. However, the number of eye blinks shows large variance along the time axis which implies it is not proper for visual fatigue monitoring system.