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Gaussian-based Filters for Elementary Motion Detector Delay Element: Modeling Spatio-Temporal Information Pathways with Elementary Motion Detection

The Hassenstein-Reichardt elementary motion detection (HR-EMD) model has been demonstrated to show its validity for modeling insect vision and its usefulness for machine vision applications. The HR-EMD uses signals from adjacent receptors with a delayed sample of the same signals to determine simple left-to-right or right-to-left motion based on the polarity of the HR-EMD output. Variations of the HR-EMD have used low-pass filters (LPFs) for the delay elements. Additional LPFs and high-pass filters (HPFs) combined with various techniques have been added to the HR-EMD to address its inability to provide accurate image velocity estimation. Proposed here is using the delays inherent in natural Gaussian-based spatio-temporal information processing pathways for the required delay element. Since such pathways are known to exist in duality in natural systems, a combination of dual EMDs is proposed as an alternate approach for precision in image velocity estimation.