Jungdong Seo

An Objective Video Quality Metric for Compressed Stereoscopic Video

Stereoscopic video create the impression of depth by using two slightly different viewpoints. Conventional video quality assessment methods for 2D video are not suitable for stereoscopic video, so a new video quality assessment model for stereoscopic video is needed. In this paper, we propose a new objective video quality metric for compressed stereoscopic video. The proposed algorithm uses blocking artifacts, blurring in edge regions and video quality difference between two views. Blocking artifacts and blurring in edge regions are distortion appeared in the compressed video, and they are widely used in conventional video quality model. Difference in video quality between two views considers 3D effect of stereoscopic video. To verify the performance of the proposed algorithm, we performed subjective evaluation of stereoscopic video, and we confirmed that the proposed algorithm is superior to the conventional algorithms in respect to correlation with the subjective evaluation.

Motion information sharing mode for depth video coding

Multi-view plus depth (MVD) video is getting more popular as a new video format for 3DTV and Free viewpoint TV. By using multi-view and depth video, it is possible to efficiently render virtual views in decoder site. In this paper, we propose a motion information sharing mode for efficient depth video coding. Because the depth video is correlated with the color video especially in object boundary areas, the motion information of the color video can be shared with the depth video. Each ma-croblock selects a mode with minimum rate-distortion cost, and the proposed mode can be used as a candidate mode. Since the proposed mode is especially selected in object boundary areas, we can obtain more coding gain. Experimental results showed coding gain up to 0.8dB, but the results depend on the quality of depth video.

Adaptive competition for motion vector prediction in multi-view video coding

An adaptive competition method is proposed in order to increase the accuracy of a motion vector (MV) prediction in multi-view video coding (MVC). Motion vector predictors for INTER mode and SKIP (DIRECT) mode is optimally selected from a given adaptive set of predictors by a slightly modified rate-distortion criterion. The adaptive set of the predictor candidates is determined, based on the analysis of the predictors according to their prediction structures. The analyzed predictors include spatial, temporal, and inter-view predictors. The proposed scheme leads to the accurate and efficient MV prediction compared to the MVC reference software, JMVC 6.0. As a result, bit-rates are decreased by nearly 5% in average, up to 7.6%, in terms of the Bjontegaard Metric.

Analysis of Motion Vector Predictor in Multiview Video Coding System

In this paper, various motion vector predictors are analyzed and their selection method is proposed for 3D video coding. In a ubiquitous multimedia system, video compression has been expected to be an important element since an available bandwidth is very limited. In the proposed method, several motion vector predictors are competed each other with the slightly modified rate-distortion criterion. Spatial, temporal, and inter-view predictors are considered as motion vector predictors to reduce spatial, temporal, and interview redundancies, respectively. The proposed method increases the motion vector coding efficiency by selecting the best motion vector predictor among them. Accordingly, overall bit rates are reduced by 5.2 % in average, up to 6.1 %compared to reference software JMVC 6.0 in terms of the Bjontegaard Metric.

Early disparity estimation skipping for multi-view video coding

Multi-view video (MVV) and multi-view plus depth video became typical formats for 3D video systems which offer more realistic visual effects for consumers. The standard for encoding of MVV, known as multi-view video coding (MVC), was produced by ISO/IEC and ITU-T and has exhibited significant compression efficiency for MVV signals. However, the high computational complexity of MVC leads to excessive power consumption and limits its applications. In this study, new fast algorithms for MVC are proposed by skipping disparity estimation prediction. According to the characteristics of the motion and disparity vectors, unnecessary disparity estimation is skipped based on the amount of motion that can be measured through the use of motion activity and SKIP mode on the temporal axis. Experimental results showed that by skipping the disparity estimation, the proposed method reduced the encoding computational complexity by nearly 73% for inter-view prediction and 38% in the overall encoding process of B-views. In addition, no noticeable visual quality degradation was observed.

Compressed Stereoscopic Video Quality Metric

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 evaluation.

Fast intra-mode decision using inter-frame correlation for H.264/AVC

The H.264/AVC standard achieves higher coding efficiency than the previous video coding standards with the rate-distortion optimization (RDO) technique which selects the best coding mode and the reference frame for each macroblock (MB). As a result, the complexity and computational load have been significantly increased. In this paper, a novel fast intra-mode decision algorithm is proposed to reduce the complexity of the video compression, which is based on the MBpsilas stationary property and the relationship of the selected modes among adjacent pictures. Experimental results show that the proposed scheme can significantly improve the speed of an intra prediction with almost zero degradation in terms of the peak signal to noise ratio (PSNR) and generated bits.

Image stitch-based multiview video coding

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 viewers 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.

An Independent Motion and Disparity Vector Prediction Method for Multiview Video Coding

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.

Multiview video codec based on KTA techniques

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.