Respiratory rate is one of important vital signs, i.e. an indication of patient's health state and its normal rates for adult person at rest may range from 12 to 20 breaths per minute (BPM). The rates may increase due to fever, illness, and other medical conditions. We report an effort to develop and calibrating a non-contact and low-cost respiratory rate monitoring system, based on digital image correlation technique using a used Microsoft Kinect camera. Steps accomplished in this reported work was designed as a hands-on training for last year student, where they can learn and grasp on how to develop a clinical instrument and to assure its measuring performance. Calibration steps were accomplished to ensure the accuracy of the monitoring results. Average measurement errors in distance determination was below 1%, meanwhile overall error in determining measured cycles were the range of 2.4% - 4.5 % (i.e. translational motion with repetition cycle of 12 - 18 cycles per minute, which is directly proportional to beat-per-minute (BPM)). The proposed system was then tested to 10 volunteers from students, to determine the volunteer's respiratory rate, i.e. either the chest and belly respiratory rates.