The central projection model commonly used to model cameras as well as projectors, results in similar advantages and disadvantages in both types of system. Considering the case of active stereo systems using a projector and camera setup, a central projection model creates several problems, among them, narrow depth range and necessity of wide baseline are crucial. In the paper, we solve the problems by introducing a light field projector, which can project a depth-dependent pattern. The light field projector is realized by attaching a coded aperture with a high frequency mask in front of the lens of the video projector, which also projects a high frequency pattern. Because the light field projector cannot be approximated by a thin lens model and a precise calibration method is not established yet, an image-based approach is proposed to apply a stereo technique to the system. Although image-based techniques usually require a large database and often imply heavy computational costs, we propose a hierarchical approach and a feature-based search for solution. In the experiments, it is confirmed that our method can accurately recover the dense shape of curved and textured objects for a wide range of depths from a single captured image.