The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
3D shape scanning with a Kinect
ACM SIGGRAPH 2011 Posters
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Proceedings of the 24th annual ACM symposium on User interface software and technology
ISMAR '11 Proceedings of the 2011 10th IEEE International Symposium on Mixed and Augmented Reality
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Inspired by the recently developed KinectFusion technique, which is able to reconstruct a 3D scene in real time through moving Kinect, we consider improving KinectFusion for 3D reconstruction of a real object. We make some adaptations to KinectFusion so as to identify the object-of-interest and separate the 3D object model from the entire 3D scene. Moreover, considering that the 3D object model generated by KinectFusion often contains some clearly visible outliers due to the noisy Kinect data, we propose a refinement scheme to remove the outliers. Our basic idea is to make use of the existing powerful 2D segmentation tool to refine the silhouette in each color image and then form visual hull via the refined dense silhouettes to improve the 3D object model. Experimental results show improved performance.