Cooperative content and radio resource allocation for visual information maximization in a digital signage scenario

Heeseok Oh, Hojae Lee, Inwoong Lee, Sanghoon Lee

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Abstract In this paper, we present a cooperative content and resource allocation algorithm that selects networks and sub-carriers for digital signage scenarios based on visual information. In these scenarios, both 2D and 3D content are handled in open space for the advertisement of commercial products. To quantify visual information, we propose a quality of visual service (QoVS) metric based on human perception. We then construct the expected QoVS problem to guarantee the maximum QoVS for service users. The QoVS is determined based on the level of 2D visual sensitivity, and on the ability to perform 3D binocular fusion by users located at various viewing distances. By utilizing the QoVS, we predict wireless packet errors and loss of visual information caused by limited radio resources. After 3D content is selected to be multicasted to users by means of the large displays, sub-carriers are optimally allocated for the remaining smartphone users to facilitate point-to-point communication through lossy wireless channels. Simulation results of the proposed scheme demonstrate the advantages of automatic control of visual information and radio resources for multiple users without additional interactions. Moreover, the method developed herein can be flexibly applied with low complexity to several visual application services provided over heterogeneous displays and channels, such as advertisements, exhibitions, and forums.

Original languageEnglish
Article number1786
Pages (from-to)24-35
Number of pages12
JournalDigital Signal Processing: A Review Journal
Publication statusPublished - 2015 Oct 1

Bibliographical note

Funding Information:
This work was supported by the ICT R&D program of MSIP/IITP ( 13-912-93-901 , Development of Context-Aware Tele-Screen System Technology).

Publisher Copyright:
© 2015 Elsevier Inc.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Applied Mathematics


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