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Motion detection has been extensively investigated [1 3].
Successful detection of motion helps to reduce the information redundancy in all of these applications and thus motion detection has become an active research issue.
However, the pyroelectric infrared (PIR) sensor, due to its inherent capability in motion detection, has the ability of directly acquiring the motion information [20 28].
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Numerous algorithms of motion detection have been presented up to now.
In reference [9], Yarovoy has examined the detection and positioning of human beings in complex environments with UWB radar and it has been shown that the range of a person varies by up to 0.6 cm because of their breathing movements, and novel motion or breathing detection has been presented on the basis of the measurements from radar return spatial variations.
Research on Drosophila's motion detection system has progressed quickly in recent years.
The researchers say that motion detection must have appeared early in the evolution of fish, and has been conserved in their descendants, including mammals.
The embedded power motion detection algorithms have to meet two requirements: limited complexity, as to comply with our CIS computational limitations and high performance.
To date, many motion detection algorithms have been developed that perform well in some types of videos but not in others.
In the few last years, the neurally inspired lateral inhibition in accumulative computation (LIAC) method and its application to the motion detection task have been introduced.
Other testing strategies such as blue-on-yellow perimetry (short-wavelength automated perimetry), frequency doubling technology (FDT), and motion detection techniques have shown to be superior to white-on-white perimetry for early visual loss detection [28].
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