Image selection for improved Multi-View Stereo

The Middlebury Multi-View Stereo evaluation [18] clearly shows that the quality and speed of most multi-view stereo algorithms depends significantly on the number and selection of input images. In general, not all input images contribute equally to the quality of the output model, since several images may often contain similar and hence overly redundant visual information. This leads to unnecessarily increased processing times. On the other hand, a certain degree of redundancy can help to improve the reconstruction in more "difficult" regions of a model. In this paper we propose an image selection scheme for multi-view stereo which results in improved reconstruction quality compared to uniformly distributed views. Our method is tuned towards the typical requirements of current multi-view stereo algorithms, and is based on the idea of incrementally selecting images so that the overall coverage of a simultaneously generated proxy is guaranteed without adding too much redundant...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Alexander Hornung, Boyi Zeng, Leif Kobbelt
• Keywords: Computer Vision, Current Multi-view Stereo, CVPR 2008, Improved Output Quality, Improved Reconstruction Quality, Middlebury Multi-view Stereo, Multi-view Stereo Algorithms