• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.375-378
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• 2005

The multi-view video is a collection of multiple videos capturing the same scene at different viewpoints. The multi-view video can be used in various applications, including free viewpoint TV and three-dimensional TV. Since the data size of the multi-view video linearly increases as the number of cameras, it is necessary to compress multi-view video data for efficient storage and transmission. The multi-view video can be coded using the concept of the layered depth image (LDI). In this paper, we describe a procedure to generate LDI from the natural multi-view video and present a method to encode multi-view video using the concept of LDI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2530-2538
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• 2015

The pixel value of depth image is depth value so that different objects which are placed on nearby position have similar pixel value. Moreover, the pixels of depth image have distinct pixel values compared to adjacent pixels while those of color image has very similar values. Accordingly distorted depth image of multiview video plus depth (MVD) needs proper error concealment methods considering the characteristics of depth image when transmission errors are happened. In this paper, classifying regions of depth image to consider edge directions and then applying adaptive error concealment methods to each region are proposed. Recovered depth images utilize with multiview video data to synthesize intermediate-view point video. The synthesized view is evaluated by objective quality metrics to demonstrate proposed method performance.

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.329-338
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• 2011

Recent augmentation reality demands more realistic multimedia data with the mixture of various media. High-technology for multimedia data which combines existing media data with various media such as audio and video dominates entire media industries. In particular, there is a growing need to serve augmentation reality, 3-dimensional contents and realtime interaction system development which are communication method and visualization tool in Internet. The existing services do not correspond to generate depth value for 3-dimensional space structure recovery which is to form solidity in existing contents. Therefore, it requires research for effective depth-map generation using 2-dimensional video. Complementing shortcomings of existing depth-map generation method using 2-dimensional video, this paper proposes an enhanced depth-map generation method that defines the depth direction in regard to loss location in a video in which none of existing algorithms has defined.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.81-83
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• 2014

This paper provides the performance comparison of selected post filters for depth map in 3D video system. In the performance comparison, the dilation filter which is currently adopted in 3D-ATM reference S/W, the bilateral filter, and the depth-oriented depth boundary reconstruction filter. In the paper, we first introduce those filters in details, and show the experimental results as post filter in 3D video system.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1711-1719
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• 2017

In this paper, we propose a method of the zoom motion estimation for the depth video coding. The proposed method calculates the zoom ratio using the average of the depth values in the current block and in the reference block. It resizes the reference block by the zoom ratio and interpolates the reference block to size of the current block. It compares the current block with the reference block that is obtained by subtracting the average of pixels from the current block to the reference block in order to find the reference block that is the best closest one to the current block. The results of the simulation for the proposed method show that the motion estimation errors are significantly reduced.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.452-454
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• 2015

This paper provides the coding performance comparisons of depth map resolution in 3D video system. In multiview plus depth map system, depth map is used for synthesis view rendering, and affects to synthesis views quality. In the paper, we show the experimental results as depth map resolution in 3D video system, and show performance variation as dilation filter.

• ETRI Journal
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• v.35 no.6
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• pp.980-989
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• 2013

The important requirements for stereo video retargeting are threefold: keeping temporal coherence, preventing depth distortion, and minimizing shape distortions of the retargeted video. To meet these requirements, the left and right video sequences are divided into groups of frames (GoFs), where the GoF is a basic unit for the seam carving and we assign a set of fixed seams for all frames within the GoF. To determine the fixed seams for each GoF, we need to find the GoF boundary in the video first. Then, the representative frame for each GoF is generated by considering the spatial saliency and temporal coherence. Also, the confidence of the stereoscopic correspondence between the left and right frames is considered to prevent depth distortion.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.1-9
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• 2009

In this paper, proposed digital image watermarking technique with lifting wavelet transformation. This watermark technique can be easily extended in video content fields. Therefore, we apply this watermark technique to layered depth image structure that is efficient compression method of multi-view video with depth images. This application steps are very simple, because watermark is inserted only reference image. And watermarks of the other view images borrow from reference image. Each view image of multi-view video may be guaranteed authentication and copyright.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.29-37
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• 2014

Since multi-view video exists a number of camera color image and depth image, it has a huge of data. Thus, a new compression technique is indispensable for reducing this data. Recently, the effective compression encoding technique for multi-view video that used in layered depth image concepts is a remarkable. This method uses several view point of depth information and warping function, synthesizes multi-view color and depth image, becomes one data structure. In this paper we use actual distance for solving overlap in layered depth image that reduce required data for reconstructing in color-based transform. In experimental results, we confirmed high compression performance and good quality of reconstructed image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.