Acoustic room modeling has several applications. Recent results using large microphone arrays show good performance, and are helpful in many applications. For example, when designing a better acoustic treatment for a concert hall, these large arrays can be used to help map the acoustic environment and aid in the design. However, in real-time applications – including de-reverberation, sound source localization, speech enhancement and 3D audio – it is desirable to model the room with existing small arrays and existing loudspeakers. In this paper we propose a novel room modeling algorithm, which uses a constrained room model and ℓ1-regularized least-squares to achieve good estimation of room geometry. We present experimental results on both real and synthetic data.