Sciweavers

Share
ICMCS
2008
IEEE

A stochastic model of selective visual attention with a dynamic Bayesian network

9 years 4 months ago
A stochastic model of selective visual attention with a dynamic Bayesian network
Recent studies in signal detection theory suggest that the human responses to the stimuli on a visual display are nondeterministic. People may attend to different locations on the same visual input at the same time. To predict the likelihood of where humans typically focus on a video scene, we propose a new stochastic model of visual attention by introducing a dynamic Bayesian network. Our model simulates and combines the visual saliency response and the cognitive state of a person to estimate the most probable attended regions. Experimental results have demonstrated that our model performs significantly better in predicting human visual attention compared to the previous deterministic model.
Derek Pang, Akisato Kimura, Tatsuto Takeuchi, Junj
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICMCS
Authors Derek Pang, Akisato Kimura, Tatsuto Takeuchi, Junji Yamato, Kunio Kashino
Comments (0)
books