HMAX model: A survey

Abstract

HMAX model is a bio-inspired feedforward architecture for object recognition, which is derived from the simple and complex cells model in cortex proposed by Hubel and Wiesel. As a hierarchical bio-based recognition model, HMAX captures the properties of primate cortex with alternated S layers and C layers, corresponding to simple cells and complex cells respectively. Although constrained by biological factors, HMAX shows satisfying performance in different fields when competing with other state-of-the-art computer vision algorithms. Insightful ideas and methods have been developed for this hierarchical model, which advances the progress of HMAX model. This paper reviews the origin of this model, as well as the improvements and modifications based on this model.