With the advances in three-dimensional (3-D) display technology, stereo conversion has attracted much attention as it can alleviate the problem of stereoscopic content shortage. In two-dimensional (2-D) to 3-D conversion, the most difficult and challenging problem is depth estimation from a single image. In order to recover a perceptually plausible depth map from a single image, a depth estimation algorithm based on a data-driven method and depth cues is presented. Based on the human visual system mechanism, which is sensitive to the foreground object, this study classifies the image into one of two classes, i.e., nonobject image and object image, and then leverages different strategies on the basis of image type. The proposed strategies efficiently extract the depth information from different images. Moreover, depth image-based rendering technology is utilized to generate stereoscopic views by combining 2-D images with their depth maps. The proposed method is also suitable for 2-D to 3-D video conversion. Qualitative and quantitative evaluation results demonstrate that the proposed depth estimation algorithm is very effective for generating stereoscopic content and producing visually pleasing and realistic 3-D views.