Infrared thermography, which has widely spread particularly during the COVID-19 period, has been effectively used for research on health monitoring and emotion estimation. Nevertheless, detecting minute temperature changes with thermography is challenging as it is disturbed by not only noise but also outside temperature surrounding the object. In this study, we demonstrate detecting face temperature variation by implementing lock-in thermography using heartbeat signals as a reference. It allows us to detect minute temperature changes, as low as $\sim$10 mK, on the forehead with a commercially available thermal camera. The proposed approach enables stable measurement of body temperature variation, showing potential for non-contact emotion estimation.