Ambient infrasound with frequency ranges well below 20 Hz is known to carry robust navigation cues that can be exploited to authenticate the location of a speaker. Unfortunately, many of the mobile devices like smartphones have been optimized to work in the human auditory range, thereby suppressing information in the infrasonic region. In this paper, we show that these ultra-low frequency cues can still be extracted from a standard smartphone recording by using acceleration-based cepstral features. To validate our claim, we have collected smartphone recordings from more than 30 different scenes and used the cues for scene fingerprinting. We report scene recognition rates in excess of 90% and a feature set analysis reveals the importance of the infrasonic signatures towards achieving the state-of-the-art recognition performance.