A Parametrizable Dataflow Implementation of Optical Flow

An increasing number of products feature complex functionality through the use of embedded computers. By collecting large amounts of data from multiple sensors and interpreting and responding to complex scenarios in realtime, such devices can become “smart. ” For a control algorithm to make a decision, data from the sensors must be processed before a certain deadline. These constraints may be hard- or soft-real-time, and a combination of SRT or HRT applications may be executed on one platform [2]. In streaming applications such as multimedia and signal processing, the dataflow model of computation (MoC) is a good fit because these applications are inherently data-driven [3]. A dataflow program consists of a graph of actors that communicate tokens through channels. An actor can only fire (execute) if all of its input tokens are available, and if there is enough space on its outgoing channels to produce all tokens. Some dataflow flavours such as mode-controlled dataflow (MCDF) and scenario-aware dataflow (SADF) can be used to deal with dynamic behaviour within one application [4, 5]. In this research we consider the processing of image data to obtain direction vector