The Extraction of Orientation and 2-D Velocity through Hierarchical Processing

This paper concerns the first functional level of visual processing in which low-level primitives are extracted for use in higher levels of processing. We constrain the computational nature of this first level such that a rich description of local intensity structure is computed while requiring no previous or concurrent interpretation. The simultaneous use and interaction of different types of visual information extracted in this way will facilitate a variety higher level tasks. We outline principles for the analysis and design of mechanisms selectively sensitive to local orientation and velocity information. We also discuss tools for the construction of such mechanisms in terms of a hierarchical computational framework. The framework consists of of cascades of explicit (convolution) and implicit (lateral interactions) spatiotemporal processing. The degree of orientation or velocity tuning can be altered by varying the number of layers in the cascade and the form of the processing at each layer.