A monocular image depth estimation method based on multi-scale CNN and continuous CRF. In the method, a CRF model is used to calculate single-point potential energy according to an output depth map of DCNN, paired sparse potential energy is calculated according to an input RGB image, and finally an optimized depth map is deduced using a maximized posterior probability (MAP) algorithm. According to the method, optimized thoughts of multi-scale CNN and continuous CRF are combined, so that not only a depth map can be estimated with a relatively high precision, the contour of the obtained depth map can also be clear. The depth estimated by means of the method has a relatively high resolution, and the obtained depth map can reserve depth detail information about all objects in a scenario, thereby having a better visual effect.
MONOCULAR IMAGE DEPTH ESTIMATION METHOD BASED ON MULTI-SCALE CNN AND CONTINUOUS CRF