In this paper, aiming at the problem of limited image acquisition location and poor reconstruction of weak texture objects in small indoor scenes, a three-dimensional reconstruction algorithm that only needs a mobile phone to acquire images is proposed. First, an active selective image matching policy is employed to reduce the number of images of pairwise matching in the original structure from motion algorithm. Then, the scale-invariant feature transform (SIFT) algorithm is improved to the Harris-SIFT algorithm to enhance real-time performance of the algorithm. Next, the predicted depth is obtained from the full consolidation neural network and fused with a multi-view stereo match algorithm to obtain more dense clouds. Finally, the reconstruction of the object is completed with a Poisson surface reconstruction algorithm. The experiment results show that the algorithm can not only effectively restore the detailed features of the object under the indoor scenes, but also has a better reconstruction effect on the surface of the weak texture objects. Compared with the original reconstruction algorithm, the time used by the algorithm is reduced by 21.07%.