Progress in image sensors and computation power has fueled studies to improve acquisition, processing, and analysis of 3D streams along with 3D scenes/objects reconstruction. The role of motion compensation/motion estimation (MCME) in 3D TV from end-to-end user is investigated in this chapter. Motion vectors (MVs) are closely related to the concept of disparities, and they can help improving dynamic scene acquisition, content creation, 2D to 3D conversion, compression coding, decompression/decoding, scene rendering, error concealment, virtual/augmented reality handling, intelligent content retrieval, and displaying. Although there are different 3D shape extraction methods, this chapter focuses mostly on shape-from-motion (SfM) techniques due to their relevance to 3D TV. SfM extraction can restore 3D shape information from a single camera data.
%0 Book
%1 farrugia2013multimedia
%A Coelho, Alessandra Martins
%A Estrela, Vania Vieira
%D 2013
%E Farrugia, Reuben A.
%E Debono, Carl J.
%I IGI Global
%K myown
%R 10.4018/978-1-4666-2660-7.ch006
%T State-of-the Art Motion Estimation in the Context of 3D TV (chapter 6), Multimedia networking and coding
%U http://arxiv.org/abs/1312.6497
%X Progress in image sensors and computation power has fueled studies to improve acquisition, processing, and analysis of 3D streams along with 3D scenes/objects reconstruction. The role of motion compensation/motion estimation (MCME) in 3D TV from end-to-end user is investigated in this chapter. Motion vectors (MVs) are closely related to the concept of disparities, and they can help improving dynamic scene acquisition, content creation, 2D to 3D conversion, compression coding, decompression/decoding, scene rendering, error concealment, virtual/augmented reality handling, intelligent content retrieval, and displaying. Although there are different 3D shape extraction methods, this chapter focuses mostly on shape-from-motion (SfM) techniques due to their relevance to 3D TV. SfM extraction can restore 3D shape information from a single camera data.
%@ 9781466626607 1466626607 9781466627222 1466627220
@book{farrugia2013multimedia,
abstract = {Progress in image sensors and computation power has fueled studies to improve acquisition, processing, and analysis of 3D streams along with 3D scenes/objects reconstruction. The role of motion compensation/motion estimation (MCME) in 3D TV from end-to-end user is investigated in this chapter. Motion vectors (MVs) are closely related to the concept of disparities, and they can help improving dynamic scene acquisition, content creation, 2D to 3D conversion, compression coding, decompression/decoding, scene rendering, error concealment, virtual/augmented reality handling, intelligent content retrieval, and displaying. Although there are different 3D shape extraction methods, this chapter focuses mostly on shape-from-motion (SfM) techniques due to their relevance to 3D TV. SfM extraction can restore 3D shape information from a single camera data.
},
added-at = {2013-12-28T18:01:15.000+0100},
author = {Coelho, Alessandra Martins and Estrela, Vania Vieira},
biburl = {https://www.bibsonomy.org/bibtex/240fc1f4a8b6503fbeb41e4be5abe2d77/vaniave},
doi = {10.4018/978-1-4666-2660-7.ch006},
editor = {Farrugia, Reuben A. and Debono, Carl J.},
interhash = {c1bcfc6a01b031f9ac0afd9bf302ccb3},
intrahash = {40fc1f4a8b6503fbeb41e4be5abe2d77},
isbn = {9781466626607 1466626607 9781466627222 1466627220},
keywords = {myown},
publisher = {IGI Global},
refid = {816315776},
timestamp = {2013-12-28T18:01:15.000+0100},
title = {State-of-the Art Motion Estimation in the Context of 3D TV (chapter 6), Multimedia networking and coding},
url = {http://arxiv.org/abs/1312.6497},
year = 2013
}