Motion Estimation Role in the Context of 3D Video

Motion Estimation Role in the Context of 3D Video

Vania Vieira Estrela, Maria Aparecida de Jesus, Jenice Aroma, Kumudha Raimond, Sandro R. Fernandes, Nikolaos Andreopoulos, Edwiges G. H. Grata, Andrey Terziev, Ricardo Tadeu Lopes, Anand Deshpande
DOI: 10.4018/IJMDEM.291556
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Abstract

The 3D end-to-end video system (i.e., 3D acquisition, processing, streaming, error concealment, virtual/augmented reality handling, content retrieval, rendering, and displaying) still needs improvements. This paper scrutinizes the motion compensation/motion estimation (MCME) impact in the 3D video (3DV) from the end-to-end users' point of view deeply. The concepts of motion vectors (MVs) and disparities are very close, and they help to ameliorate all the stages of the end-to-end 3DV system. The high-efficiency video coding (HEVC) video codec standard is taken into consideration to evaluate the emergent trend towards computational treatment throughout the cloud whenever possible. The tight bond between movement and depth affects 3D information recovery from these cues and optimizes the performance of algorithms and standards from several parts of the 3D system. Still, 3DV lacks support for engaging interactive 3DV services. Better bit allocation strategies also ameliorate all 3D pipeline stages while being attentive to cloud-based deployments for 3D streaming.
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1. Introduction

3D-TVs face technological issues regarding rendering and displaying. Some areas where 3D information is vital are biomedical applications, cultural heritage investigations, and remote sensing. The H.264/AVC (Estrela, & Coelho, 2013; Marins & Estrela, 2017), the JMVC, and the High-Efficiency Video Coding (HEVC or H.265) standards brought numerous 3D Video (3DV) friendly deployments. Right now, new video deployments will likely use HEVC. H.265 provides some necessary expansions, specific multiview HEVC coding structures, standardization, and compensations, despite challenges for 3DV end-to-end systems' pipeline rationale that outsmarts H.264/AVC codec.

Figure 1 depicts 3DVs' acquisition and creation. Figure 2 clarifies reception/delivery with different 3DV renderings/displays. The complete 3D streaming system comprises acquisition, encoding, broadcast, receiving, decoding, Error Concealment (EC), rendering, and reproduction. EC can happen in any of the stages.

Figure 1.

3DV transmission

IJMDEM.291556.f01
Figure 2.

3DV reception

IJMDEM.291556.f02

Synchronized cameras generate/assemble the 3DV from content producers by combining several sources, e.g., live Computer Graphics (CG), and uncompressed streams, to encode them. Afterward, compressed scenes go to distinct network channels. Networked decoders recover individual streams at the receiver and forward the content to proper rendering. They can also receive virtual-view parameters with distributed scalability of the sampled, transmitted, and displayed views.

This paper explores Motion Compensation, and Motion Estimation (MCME) for end-to-end 3DV systems since motion data helps with the massive data from acquiring, handling, analyzing, transforming, and recreating 3D from video streams.

Section 2 overviews MCME and its relation to 3DV. Section 3 depicts the HEVC codec. Section 4 describes all stages of an end-to-end 3DV system. Future 3DV trends appear in Section 5. Section 6 states the major conclusions on MCME.

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2. Background And Definitions

Motion Vectors (MVs) help predict other images via Motion Compensation (MC). Motion Estimation (ME) counts on previous or future frames to pinpoint unchanged blocks. MC and ME are vital parts of video compression in many codecs.

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