Bio-Inspired Visual Analytics
Humans are adept at complex visual tasks such as detection, tracking and recognition. The first aim of this project is to understand humans visual attention mechanism and the factors influencing it. In particular we investigate the importance of scene context in attention modeling. We have also developed human attention inspired models to build semantic priors for text detection which outperforms state-of-the-art. Additionally, we have also improved object detection and video object segmentation using eye tracking data.