Inter-camera coding of multi-view video using layered depth image representation

Authors:
Seung-Uk Yoon;Eun-Kyung Lee;Sung-Yeol Kim;Yo-Sung Ho;Kugjin Yun;Sukhee Cho;Namho Hur
Affiliations:
Department of Information and Communications, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea;Department of Information and Communications, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea;Department of Information and Communications, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea;Department of Information and Communications, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea;Broadcasting System Research Group, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea;Broadcasting System Research Group, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea;Broadcasting System Research Group, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea
Venue:
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Year:
2006

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Abstract

The multi-view video is a collection of multiple videos, capturing the same scene at different viewpoints. If we acquire multi-view videos from multiple cameras, it is possible to generate scenes at arbitrary view positions. It means that users can change their viewpoints freely and can feel visible depth with view interaction. Therefore, the multi-view video can be used in a variety of applications including three-dimensional TV (3DTV), free viewpoint TV, and immersive broadcasting. However, since the data size of the multi-view video linearly increases as the number of cameras, it is necessary to develop an effective framework to represent, process, and display multi-view video data. In this paper, we propose inter-camera coding methods of multi-view video using layered depth image (LDI) representation. The proposed methods represents various information included in multi-view video hierarchically based on LDI. In addition, we reduce a large amount of multi-view video data to a manageable size by exploiting spatial redundancies among multiple videos and reconstruct the original multiple viewpoints successfully from the constructed LDI.