Object Tracking on Embedded Hardware

Abstract

Object tracking is an extensively researched subject within the field of computer vision, in reference to the large number of published contributions in major computer vision conference proceedings and journals every year. This chapter presents object tracking achievements over the past years as well as research trends. It attempts to give a structured overview of a broad spectrum of modern approaches focusing on embedded platforms, where the application of computer vision techniques faces a challenge due to the limitation of available resources, mainly memory and CPU power. Constraints imposed by the embedded platforms are described, relevant issues from an application-oriented point of view are reviewed, and approaches using data originating from event-based cameras and systems are discussed. Given the vast pool of available tracking algorithms, it is necessary to quantitatively assess the outcome of different tracking methodologies, which leads us to the issue of performance evaluation. A summary of tracking evaluation frameworks, associated metrics, strengths, and weaknesses of the presented approaches is also discussed. A discussion of future trends concludes this chapter.