Selective Visual Attention: Computational Models and Applications

9.1 Summary

The book has three parts: concepts and the background of visual attention (Chapters 1 and 2), computational models and performance benchmarking (Chapters 3, 4, 5 and 6) and applications of visual attention modelling (Chapters 7 and 8).

Chapter 1 in Part I introduces the definition and classification of visual attention, as well as its contributions to visual information processing. Three principal concepts result from intuitional experiments and records of eye movements: (1) Visual attention is in existence universally. (2) Visual attention can be classified into different types: pre-attention, attention and post attention, based on the order of processing stage; bottom-up and top-down attention according to different driving sources – external data driven for bottom-up and internal task (motivation) driven for top-down; parallel and serial attention in the light of different processing manners; overt and covert attention based on whether there is eye movement or not. (3) Change blindness and inhibition of return exist in visual attention.

The foundation on which to build computational attention models is presented in Chapter 2 of Part I. The basis of biology comes from two aspects: one is from physiology and anatomy, and the other from psychological and neuroscience studies. In addition, the ground of engineering is from the theory of statistical signal processing.

9.1.1 Research Results from Physiology and Anatomy

Visual information processing in low-level cortex ...