Central and peripheral vision for scene recognition: A neurocomputational modeling exploration

Understand

What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy.

• However, central vision is more efficient for scene recognition than peripheral, based on the amount of visual area needed for accurate recognition.
• In this study, we model and explain the results of Larson and Loschky (2009) using a neurocomputational modeling approach.
• We show that the advantage of peripheral vision in scene recognition, as well as the efficiency advantage for central vision, can be replicated using state-of-the-art deep neural network models.