Mesh-Based Depth Coding for 3D Video using Hierarchical Decomposition of Depth Maps

Kim, Sung-Yeol; Ho, Yo‐Sung

doi:10.1109/icip.2007.4379779

Cited by 36 publications

(19 citation statements)

References 4 publications

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“…Many approaches have been studied in the literature, such as the multiview format [5], light fields [6] or even mesh-based techniques [7]. All these representations contain two types of data: i) the color or luminance information, which is classically described by 2D images; ii) the geometry information that describes the scene's 3D characteristics, represented by 3D coordinates, depth maps or disparity vectors.…”

Section: Ultiviewmentioning

confidence: 99%

“…Hence, their objective is to preserve the sharpness of the edges, while spending few bits on the flat or smooth parts. Examples of such coding tools that have been proposed recently include meshes [7], platelets [23], shape-adaptive wavelets [24], new block formats [25], graph-based transforms [26] and coding of depth edges [27]. These tools indeed lead to better view synthesis performance using lossily encoded depth.…”

Section: Related Workmentioning

confidence: 99%

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Graph-Based Representation for Multiview Image Geometry

Maugey

Ortega

Frossard

2015

IEEE Trans. on Image Process.

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Abstract-In this paper, we propose a new geometry representation method for multiview image sets. Our approach relies on graphs to describe the multiview geometry information in a compact and controllable way. The links of the graph connect pixels in different images and describe the proximity between pixels in 3D space. These connections are dependent on the geometry of the scene and provide the right amount of information that is necessary for coding and reconstructing multiple views. Our multiview image representation is very compact and adapts the transmitted geometry information as a function of the complexity of the prediction performed at the decoder side. To achieve this, our graph-based representation (GBR) carefully selects the amount of geometry information needed before coding. This is in contrast with depth coding, which directly compresses with losses the original geometry signal, thus making it difficult to quantify the impact of coding errors on geometry-based interpolation. We present the principles of this GBR and we build an efficient coding algorithm to represent it. We compare our GBR approach to classical depth compression methods and compare their respective view synthesis qualities as a function of the compactness of the geometry description. We show that GBR can achieve significant gains in geometry coding rate over depth-based schemes operating at similar quality. Experimental results demonstrate the potential of this new representation.Index Terms-Multiview image coding, 3D representation, view prediction, graph-based representation.

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Section: Ultiviewmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Graph-Based Representation for Multiview Image Geometry

Maugey

Ortega

Frossard

2015

IEEE Trans. on Image Process.

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“…The method derives block partition from the video reference frame corresponding to a depth map and utilizes the partition information to coding the depth map. Kim and Ho [14] proposed a new scheme to compress depth information of a mesh-based 3D video. Unlike previous mesh-based depth coding methods, they compress [6] present a unified optimization framework to combine two depth map compression techniques -graph based transform (GBT) and transform domain sparsification (TDS) for optimal coding performance.…”

Section: A Stereo Video Codingmentioning

confidence: 99%

A Compact Representation for Compressing Converted Stereo Videos

Zhang¹,

Zhou²,

Wang

et al. 2014

IEEE Trans. on Image Process.

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Abstract-We propose a novel representation for stereo videos namely 2D-plus-depth-cue. This representation is able to encode stereo videos compactly by leveraging the by-product of a stereo video conversion process. Specifically, the depth cues are derived from an interactive labeling process during 2D-to-stereo video conversion-they are contour points of image regions and their corresponding depth models, and so forth. Using such cues and the image features of 2D video frames, the scene depth can be reliably recovered. Experimental results demonstrate that the bit rate can be saved about 10%-50% in coding a stereo video compared with multiview video coding and the 2D-plusdepth methods. In addition, since the objects are segmented in the conversion process, it is convenient to adopt the region-ofinterest (ROI) coding in the proposed stereo video coding system. Experimental results show that using ROI coding, the bit rate is reduced by 30%-40% or the video quality is increased by 1.5-4 dB with the fixed bit rate.Index Terms-Stereo video representation, stereo video coding, depth cue.

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“…In contrast to pixel-based depth compression methods, a conversion of the scene geometry into computer graphics based meshes and the application of mesh-based compression technology was described in [23].…”

Section: ) Advanced Depth Codingmentioning

confidence: 99%

3D-TV Content Storage and Transmission

Vetro

Tourapis

Müller

et al. 2011

IEEE Trans. on Broadcast.

125

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There exist a variety of ways to represent 3D content, including stereo and multiview video, as well as frame compatible and depth-based video formats. There are also a number of compression architectures and techniques that have been introduced in recent years. This paper provides an overview of relevant 3D representation and compression formats. It also analyzes some of the merits and drawbacks of these formats considering the application requirements and constraints imposed by different storage and transmission systems. IEEE Transactions on BroadcastingThis work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved.

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Mesh-Based Depth Coding for 3D Video using Hierarchical Decomposition of Depth Maps

Cited by 36 publications

References 4 publications

Graph-Based Representation for Multiview Image Geometry

Graph-Based Representation for Multiview Image Geometry

A Compact Representation for Compressing Converted Stereo Videos

3D-TV Content Storage and Transmission

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