KinectFusion: Real-time dense surface mapping and tracking
ISMAR '11 Proceedings of the 2011 10th IEEE International Symposium on Mixed and Augmented Reality
RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
International Journal of Robotics Research
Dense scene reconstruction with points of interest
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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3D reconstruction of real world objects is a fundamental problem in computer vision and computer graphics. It is a challenge for high fidelity reconstruction with consumer-grade depth camera, e.g. Microsoft Kinect on large scale scene. A divide-and-conquer approach could both preserve local geometry details of scene objects and global consistency of the whole scene, thus is superior to existing GPU based real-time/global optimization based offline methods. In this paper, we extend the state-of-the-art in two folds. First, more fine grit scene segmentation is conducted for better local details preservation. Second, a scene analysis procedure is proposed for more reasonable global error spread. Preliminary experiments show that our method achieves more convincing reconstruction results.