EXTREME VALUE THEORY-BASED METHODS FOR VISUAL RECOGNITION

A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the average. From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy