We present a method to make an accurate and dense reconstruction from the input of video captured by a free moving handheld camera in real time. By the method firstly, the positions of the camera and sparse 3D points are estimated by simultaneous localization mapping. Then the depth maps of selected reference frames are computed from corresponding camera bundles. Lastly a novel linear algorithm is also proposed to integrate all the depth maps into dense meshes partially. The main contributions of this paper are in the following points: the reference frames and corresponding camera bundles are able to be selected automatically, then accurate and smooth depth maps are generated in real time, and the depth maps are merged into a dense mesh by using a linear algorithm based on the error clouds optimization. Our algorithm is implemented on dual CPU and graphics processing unit in a parallel framework for improving the performance.