Implementation and optimisation of a video object segmentation algorithm on an embedded DSP platform

Abstract

The Gaussian mixture model (GMM) is a popular algorithm employed for visual scene segmentation. In this paper we present an investigation into a real-time implementation of the algorithm on an embedded TI DM642 DSP platform suitable for outdoor and indoor surveillance applications. We present a number of possible implementations in fixed-point arithmetic and investigate their respective performances over varying model parameters. We discuss a number of different optimisations capitalising on the DSP architecture that lead to a flexible and efficient video object segmentation working prototype system.