Motion Estimation Role in the Context of 3D Video

Vania Estrela (), Maria Aparecida de Jesus, Jenice Aroma, Kumudha Raimond, Sandro R. Fernandes, Nikolaos Andreopoulos, Edwiges G. H. Grata, Andrey Terziev, Ricardo Tadeu Lopes and Anand Deshpande
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Maria Aparecida de Jesus: Universidade Federal Fluminense (UFF), Brazil
Jenice Aroma: Karunya University, India
Kumudha Raimond: Karunya Institute of Technology and Sciences, India
Sandro R. Fernandes: Instituto Federal de Educacao, Ciencia e Tecnologia do Sudeste de Minas Gerais, Brazil
Nikolaos Andreopoulos: Technological Institute of Iceland, Iceland
Edwiges G. H. Grata: Universidade Federal Fluminense (UFF), Brazil
Andrey Terziev: TerziA, Bulgaria
Ricardo Tadeu Lopes: Federal University of Rio de Janeiro (UFRJ), Brazil
Anand Deshpande: Angadi Institute of Technology and Management, Belagavi, India

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2021, vol. 12, issue 3, 16-38

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.

Date: 2021
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International Journal of Multimedia Data Engineering and Management (IJMDEM) is currently edited by Chengcui Zhang

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