Real-time Camera Guidance for 3d Scene Reconstruction

We propose a framework for operator guidance during the image acquisition process for reliable multi-view stereo reconstruction. Goal is to achieve full coverage of the object and sufficient overlap. Multi-view stereo is a commonly used method to reconstruct both camera trajectory and 3D object shape. After determining an initial solution, a globally optimal reconstruction is usually obtained by executing a bundle adjustment involving all images. Acquiring suitable images, however, still requires an experienced operator to ensure accuracy and completeness of the final solution. We propose an interactive framework for guiding unexperienced users or possibly an autonomous robot. Using approximate camera orientations and object points we estimate point uncertainties within a sliding bundle adjustment and suggest appropriate camera movements. A visual feedback system communicates the decisions to the user in an intuitive way. We demonstrate the suitability of our system with a virtual image acquisition simulation as well as in real-world scenarios. We show that when following the camera movements suggested by our system, the proposed framework is able to generate good approximate values for the bundle adjustment, leading to accurate results compared to ground truth after few iterations. Possible applications are non-professional 3D acquisition systems on low-cost platforms like mobile phones, autonomously navigating robots as well as online flight planning of unmanned aerial vehicles.