TY - GEN
T1 - View selection policy for multi-view video delivery
AU - Chakareski, Jacob
PY - 2013/10/18
Y1 - 2013/10/18
N2 - We derive an optimization framework for computing a view selection policy for streaming multi-view content over a bandwidth constrained channel. The optimization allows us to determine the decisions of sending the packetized data such that the end-to-end reconstruction quality of the content is maximized, for the given bandwidth resources. Two prospective multi-view content representation formats are considered: MVC and video plus depth. For each, we formulate directed graph models that characterize the interdependencies between the data units comprising the content. For the video plus depth format, we develop a spatial error concealment strategy that reconstructs missing content at the client based on received data from other views. We design multiple techniques to solve the optimization problem of interest either exactly or approximatively, at lower complexity. In conjunction, we derive a spatial model of the reconstruction error for the multi-view content that we employ to reduce the computational requirements of the optimization. We study the performance of our framework via simulation experiments. Significant gains in terms of rate-distortion efficiency are observed over a content-agnostic reference technique.
AB - We derive an optimization framework for computing a view selection policy for streaming multi-view content over a bandwidth constrained channel. The optimization allows us to determine the decisions of sending the packetized data such that the end-to-end reconstruction quality of the content is maximized, for the given bandwidth resources. Two prospective multi-view content representation formats are considered: MVC and video plus depth. For each, we formulate directed graph models that characterize the interdependencies between the data units comprising the content. For the video plus depth format, we develop a spatial error concealment strategy that reconstructs missing content at the client based on received data from other views. We design multiple techniques to solve the optimization problem of interest either exactly or approximatively, at lower complexity. In conjunction, we derive a spatial model of the reconstruction error for the multi-view content that we employ to reduce the computational requirements of the optimization. We study the performance of our framework via simulation experiments. Significant gains in terms of rate-distortion efficiency are observed over a content-agnostic reference technique.
UR - http://www.scopus.com/inward/record.url?scp=84890521084&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890521084&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2013.6638356
DO - 10.1109/ICASSP.2013.6638356
M3 - Conference contribution
AN - SCOPUS:84890521084
SN - 9781479903566
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 3736
EP - 3740
BT - 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
T2 - 2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Y2 - 26 May 2013 through 31 May 2013
ER -