Real-time tracking of visually attended objects in virtual environments and its application to LOD

Sungkil Lee, G. J. Kim, Seungmoon Choi

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.

Original languageEnglish
Article number4531740
Pages (from-to)6-19
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number1
Publication statusPublished - 2009 Jan

Bibliographical note

Funding Information:
The authors would like to thank the four reviewers for their insightful comments and Toru Miyazawa at Toucan Co. for granting use of the fish models. This work was supported in parts by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (R01-2006-000-11142-0, R01-2006-000-10808-0, and R0A-2008-000-20087-0). Correspondence concerning this article should be addressed to Gerard J. Kim.


  • Bottom-up feature
  • Level of detail
  • Saliency map
  • Top-down context
  • Virtual environment
  • Visual attention

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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