  This paper deals with the Compressive Sensing implementation in the Face
Recognition problem. Compressive Sensing is new approach in signal processing
with a single goal to recover signal from small set of available samples.
Compressive Sensing finds its usage in many real applications as it lowers the
memory demand and acquisition time, and therefore allows dealing with huge data
in the fastest manner. In this paper, the undersampled signal is recovered
using the algorithm based on Total Variation minimization. The theory is
verified with an experimental results using different percentage of signal
samples.
