Without knowing the intrinsic light-field parameters, a calibration process was conducted for depth estimation by a focused micro light-field camera based on virtual depth. In order to derive the functional relation between virtual depth and real depth, a light-field imaging model was established according to the Gaussian optics. A single corner calibration board was imaged at various depth distances. The corner point was multi-imaged in several macro-pixels, and the distance between adjacent redundant image points varied according to the depth value. By using an image matching algorithm, the distance between adjacent redundant image points as well as the virtual depth was calculated. After that, the curve for the relation between the virtual depth and corresponding real depth was fitted. Based on this fitted function, the resolution of depth estimation at different depths was analyzed. By capturing a slanted chessboard target, the depth estimation error was obtained. When the working distance toward the lens is within the range of 2 mm (10 times DOF), the error of depth estimation is lower than 5.35%.