A Visual Attention Model for Dynamic Scenes Based on Two-Pathway Processing in Brain Export

@article{citeulike:4949697, abstract = {In this paper, a visual attention model for dynamic scenes based on two-pathway processing in brain is proposed. A saliency map is created to measure the static features, and a motion conspicuity map is created to measure the dynamic feature. Both maps are integrated in an IFNN which is employed to simulate the interactive aspects of two-pathway processing in brain. Selection of attention is accomplished by the interspike interval of the neural network. The experiments results show the effective and efficient performance of the model.}, address = {Los Alamitos, CA, USA}, author = {Chen, Jiawei and Zhou, Changle and Lin, Kunhui and Qu, Yanyun}, citeulike-article-id = {4949697}, citeulike-linkout-0 = {http://doi.ieeecomputersociety.org/10.1109/ICNC.2008.392}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/ICNC.2008.392}, doi = {10.1109/ICNC.2008.392}, isbn = {978-0-7695-3304-9}, journal = {International Conference on Natural Computation}, keywords = {attention, eye, movement, saliency, visual}, pages = {128--132}, posted-at = {2009-06-25 02:35:40}, priority = {2}, publisher = {IEEE Computer Society}, title = {A Visual Attention Model for Dynamic Scenes Based on Two-Pathway Processing in Brain}, url = {http://dx.doi.org/10.1109/ICNC.2008.392}, volume = {6}, year = {2008} }

TY - JOUR ID - citeulike:4949697 L3 - citeulike-article-id:4949697 N2 - In this paper, a visual attention model for dynamic scenes based on two-pathway processing in brain is proposed. A saliency map is created to measure the static features, and a motion conspicuity map is created to measure the dynamic feature. Both maps are integrated in an IFNN which is employed to simulate the interactive aspects of two-pathway processing in brain. Selection of attention is accomplished by the interspike interval of the neural network. The experiments results show the effective and efficient performance of the model. JF - International Conference on Natural Computation SN - 978-0-7695-3304-9 AD - Los Alamitos, CA, USA EP - 132 TI - A Visual Attention Model for Dynamic Scenes Based on Two-Pathway Processing in Brain PB - IEEE Computer Society VL - 6 SP - 128 KW - attention KW - eye KW - movement KW - saliency KW - visual AU - Chen, Jiawei AU - Zhou, Changle AU - Lin, Kunhui AU - Qu, Yanyun PY - 2008/// UR - http://dx.doi.org/10.1109/ICNC.2008.392 ER -