In recent years, smart devices are integrated into an image processing and display system for complex information, which involves real-time computing, motion tracking, pattern recognition, image projection, feature extraction, and computer science. 3D model generation by amateur devices becomes essential and highly demanded. In this study, 3D scene models were generated through reconstruction pipeline, which integrates structure from motion (SFM), multi-view stereo (MVS), and Poisson surface reconstruction (PSR) on images shot by a camera and four smart phones, without need of a priori internal and external camera parameters. In this research, the result of camera calibration is regard to represent the quality of 3D reconstruction. Four kinds of smart phones and amateur camera Canon EOS 500D+18mm are calibrated by photogrammetric calibration and SFM. The focal lengths generated by the photogrammetric calibration are considered as true values. The equivalent focal lengths of IPHONE_4S, SAMSUNG_S2, SONY_ACROS, SAMSUNG_GT-5660 and Canon EOS 500D calculated by SFM are 32.54 (mm), 36.52 (mm), 34.47 (mm), 36.12 (mm), and 28.37 (mm), respectively. The result shows that all smartphones can generate 3D models with acceptable accuracy and precision. This paper demonstrates that applying photos shot by smartphones for 3D reconstruction is available and feasible.