In this paper, we present the modelling of a real-time tracking system on a Multi-Processor System on Chip (MPSoC).
Our final goal is to build a more complex computer vision system (CVS) by integrating several applications in a modular
way, which performs different kind of data processing issues but sharing a common platform, and this way, a solution for
a set of applications using the same architecture is offered and not just for one application. In our current work, a visual
tracking system with real-time behaviour (25 frames/sec) is used like a reference application, and also, guidelines for our
future CVS applications development. Our algorithm written in C++ is based on correlation technique and the threshold
dynamic update approach. After an initial computational complexity analysis, a task-graph was generated from this
tracking algorithm. Concurrently with this functionality correctness analysis, a generic model of multi-processor
platform was developed. Finally, the tracking system performance mapped onto the proposed architecture and shared
resource usage were analyzed to determine the real architecture capacity, and also to find out possible bottlenecks in
order to propose new solutions which allow more applications to be mapped on the platform template in the future.