**1. Introduction**

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Motion estimation is a low-level vision task which manages a high number of applications as sport tracking, surveillance, security, industrial inspection, robotics, navigation, optics, medicine and so on. Unfortunately, many times it is unaffordable to implement a fully functional embedded system for real-time operation which works in a while with enough accuracy due the nature and complexity of the signal processing operations involved.

In this chapter, we will introduce different motion estimation systems and their implementation when real-time is required. For the sake of clarity, it will be previously shown a general description of the motion estimation paradigm. Subsequently, three systems regarding low-level and mid-level vision domain will be explained.

The present chapter is thus organized as follows, after an introductory part, the second section is regarding the motion estimation and optical flow paradigms, the similarities and differences to understand the real-time methods and algorithms. Later will be performed a classification of motion estimation systems according different families and enhancements for further approaches. This second section is finished with a plethora of real-time implementations of the systems explained previously.

The third section focuses on three different case studies of real-time optical flow systems developed by the authors, where also are presented the throughput and resource consuming data from a reconfigurable platform (FPGA-based) used in the implementation.

The fourth section analyses the performance and the resources consumed by each one of this three specific real-time implementations. The rest of the sections, fifth to seventh, approaches the conclusion, the acknowledgements and the bibliography, respectively.
