Motile cilia, hair-like structures on epithelial cells, oscillate asymmetrically through effective and recovery strokes to generate ciliary flow for clearance of mucus in the respiratory tract. Failure in clearing mucus results in stacking of thick mucus layer containing pathogens and dust, which lead to infection, difficulty in breathing, and inflammation. In predicting malfunction in the mucociliary clearance, characterization and evaluation of the ciliary beating motion is critical. Currently available tools indirectly characterize ciliary beating from video of ciliary field using high magnification objective and complicated image processing. Here, we attached fluorescent micro particles onto cilia and directly track their trajectories to characterize ciliary beating. Using ciliated primary human nasal epithelial cells, we analyzed beating motion of nasal cilia in terms of beating frequency, velocity and orientation. Acquired average beating frequency and the ratio of velocities between effective and recovery strokes were physiologically relevant. Our technique will be helpful for the acquisition of ciliary beating trajectories and motion analysis without implementing high magnification objective or complex imaging analysis.