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Selective Visual Attention: Computational Models and Applications by Weisi Lin, Liming Zhang

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2.6 Statistical Signal Processing

It is known that a cell's response in the brain is a spiking train with almost out-of-order timing (random), so its response strength has to be estimated by its mean firing rate within a fixed interval. Human vision receives a large number of signals from the environment, and this results in a great deal of cells firing in various areas of the brain at all times. How can we depict the activity of the cell population across time and space? From the view of signal processing and computer vision, the concepts of probability distribution, other statistical properties and signal detection and estimation with statistical signal processing theory need to be considered in visual attention modelling.

Many computational visual attention models are based on information theory and statistical signal processing, and detailed discussions will be given in the next chapter. This section simply introduces the relationship between visual attention and these relevant theories, which mainly consist of the following three aspects.

1. Signal detection theory and visual attention: if the target in a scene is considered as a signal and the distractors or background is regarded as noise, visual search or visual attention will become a signal detection issue. Thus, the analysis methodology in signal detection theory can be used in visual attention [121].
2. Estimation theory and visual attention: for the time sequence of scenes, novel objects that have not appeared in ...

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