Abstract: According to the psychology analysis of human visual perceiving,people tend to pay more attention to the foreground than the background in watching videos.In this paper,a novel 2D to 3D conversion method based on segmenting the foreground from the background is proposed.Firstly,the moving objects are detected by background model and refined by attention model so as to extract the foreground objects in interests.Secondly,every object in the background is found by machine learning method,and the depth of the background object is estimated based on the pin-hole camera model.Thirdly,the depth of the foreground is estimated by its location and the frame coherence.Finally,the depth of foreground and background are integrated.The experiments showed that our algorithm can be easily applied to many scenes and the result of depth estimation reflects the location of each object in the real world exactly.