Weakly Constrained3D Surface Reconstruction Based On Monocular Vision

Three-dimention reconstruction is a classical problem in computer vision. Due tothe general and convenient application of the monocular camera, we only focus on3Dsurface reconstruction based on monocular vision technique in this paper.There are many constraints in the classical3D reconstruction based on monocularvision technology, especially for the constraints of lighting conditions, which willgenerate the difficulty in configuration of light sources and equipments. In this paper,we mainly focus on reducing these constraints, and making3D surface reconstructionbased on monocular vision more robust under the complex lighting conditions.Moreover the interactive reflection and shadow in3D reconstruction will also bediscussed. The main work and innovation points include:(1) The main algorithms based on monocular vision have been introduced, whichare the typical methods and have reflected the newest technology in the research ofmonocular vision. In this paper, we present our new method based on the ideas ofthese algorithms.(2) We discuss the commonly used lighting models and analyze theircharacteristics. By using these lighting models, the input images have been renderedunder various kinds of lighting conditions. Through analyzing the rendering error, themost robust lighting model has been selected to simulate the lighting condition of theinput image.(3) An uncalibrated PMS algorithm based on the reference object has beenproposed. Firstly, the target object and the reference object are put in the same scene,and the multiple images will be captured by making different lighting conditions.Then using the reference object, the lighting matrix will be estimated and the shape ofthe target object will be reconstructed quickly.(4) A fast uncalibrated PMS algorithm for estimating human surface normal hasbeen proposed by merging the classical PMS and the method of estimating lightingparameters. The effectiveness of this algorithm has been verified by the experimentsin the YaleB and BU3D databases.(5) A new framework of3D face reconstruction has been propsed based on a coupled statistical model. The3D shape can be estimated from a face image, whichhas the different lighting condition with the images in training set. The reconstructedresults are more accurate than the state of the art method.(6) An effective method has been presented for the same kind of objects. Thestitching and optimization has been used in the proposed method. An input rocktexture has been tested and compared with the method of SFS. The experimetnsverified the more effective of our proposed method than that of SFS.We can reconstruct the3D shape of the object from the captured images bymonocular camera. Then the intrinsic features of the object will be restored and not beaffected by the change of vision angle or the lighting conditons, which has animportant application prospection for coal, drilling, exploration and archaeology etc.