Live cell imaging, which allows researchers to observe the surface of individual cells in experimental conditions, has helped biologists investigate the regulation of cell signaling machinery. In particular, receptor proteins on the surface of the cell are key to cellular responses to external stimuli and to cell-to-cell communication, and endocytic and exocytic pathways play an important role in regulating cell responses. Cell-surface imaging has clarified regulatory mechanisms for endocytosis and identified different classes of endocytic events, but exocytic events are less studied and less understood. In this work, we develop a functional PCA time series representation of exocytic event images, allowing us to study the dynamics of these events and identify different classes of events by clustering their time series. These classes capture differences in the diffusion of receptor proteins from exocytic vesicles, and we show differences in class membership between different receptors, suggesting pathway diversity. Finally, we show that our representation can aid in automatic detection of exocytic events, helping researchers collect more data with less time-intensive hand-labeling.