For most imaging systems, there is a trade-off between spatial resolution, temporal resolution, and signal-to-noise ratio. Such a trade-off is particularly severe in single-pixel imaging systems, given the limited throughput of the only one available pixel. Here we report a real-time single-pixel imaging method that can adaptively balance the spatial resolution, temporal resolution, and signal-to-noise ratio of the imaging system according to the changes in the target scene. When scene changes are detected, the dynamic imaging mode will be activated. The temporal resolution will be given high priority and real-time single-pixel imaging will be conducted at a video frame rate (30 frames/s) to visualize the object motion. When no scene changes are detected, the static imaging mode will be activated. The spatial resolution and the signal-to-noise ratio will be progressively built up to resolve fine structures and to improve image quality. The proposed method not only adds practicability to single-pixel imaging, but also generates a new, to the best of our knowledge, insight in data redundancy reduction and information capacity improvement for other computational imaging schemes.