Breathing waveform extracted via nasal thermistor is the most common method to study respiratory function in sleep studies. In essence, this is a temporal waveform of mean temperatures in the nostril region that at every time step collapses two-dimensional data into a single point. Hence, spatial heat distribution in the nostrils is lost along with valuable functional and anatomical cues. This article presents the construction and experimental validation of a spatiotemporal profile for the breathing function via thermal imaging of the nostrils. The method models nasal airflow advection by using a front-propagating level set algorithm with optimal parameter selection. It is the first time that the full two-dimensional advantage of thermal imaging is brought to the fore in breathing computation. This new multi-dimensional measure is likely to bring diagnostic value in sleep studies and beyond.