Robust 3D reconstruction from uncalibrated small motion clips

Small motion can be induced from burst video clips captured by a handheld camera when the shutter button is pressed. Although uncalibrated burst video clip conveys valuable parallax information, it generally has small baseline between frames, making it difficult to reconstruct 3D scenes. Existing methods usually employ a simplified camera parameterization process with keypoint-based structure from small motion (SFSM), followed by a tailored dense reconstruction. However, such SFSM methods are sensitive to insufficient or unreliable keypoint features, and the subsequent dense reconstruction may fail to recover the detailed surface. In this paper, we propose a robust 3D reconstruction pipeline by leveraging both keypoint and line segment features from video clips to alleviate the uncertainty induced by small baseline. A joint feature-based structure from small motion method is first presented to improve the robustness of the self-calibration with line segment constraints, and then, a noise-aware PatchMatch stereo module is proposed to improve the accuracy of the dense reconstruction. Finally, a confidence weighted fusion process is utilized to further suppress depth noise and mitigate erroneous depth. The proposed method can reduce the failure cases of self-calibration when the keypoints are insufficient, while recovering the detailed 3D surfaces. In comparison with state of the arts, our method achieves more robust and accurate 3D reconstruction results for a variety of challenging scenes.