Image-based motion estimation in a stream programming language

Abstract

In this thesis, a computer vision application was implemented in the StreamIt language. The reference application was an image-based motion estimation algorithm written in MATLAB. The intent of this thesis is to contribute a case study of StreamIt, an architecture-independent language designed for stream programming. In particular, it observes StreamIt's ability to preserve block structure and to handle otherwise complicated functionality in an elegant fashion, especially in comparison to the reference implementation, coded in MATLAB. Furthermore, we observe a runtime of the StreamIt-coded application 2% faster than that of MATLAB. Lastly, the potentials of boosted performance with parallelization of subroutines within the program are discussed.