A multi-view approach to motion and stereo
- 20 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 157-163 Vol. 1
- https://doi.org/10.1109/cvpr.1999.786933
Abstract
This paper presents a new approach to computing dense depth and motion estimates from multiple images. Rather than computing a single depth or motion map from such a collection, we associate motion or depth estimates with each image in the collection (or at least some subset of the images). This has the advantage that the depth or motion of regions occluded in one image will still be represented in some other image. Thus, tasks such as novel view interpolation or motion-compensated prediction can be solved with greater fidelity. Furthermore, the natural variation in appearance between different images can be captured. To formulate motion and structure recovery, we cast the problem as a global optimization over the unknown motion or depth maps, and use robust smoothness constraints to constrain the space of possible solutions. We develop and evaluate some motion and depth estimation algorithms based on this framework.Keywords
This publication has 20 references indexed in Scilit:
- A multi-view approach to motion and stereoPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Stereo matching with transparency and mattingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Photorealistic scene reconstruction by voxel coloringPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Layered depth imagesPublished by Association for Computing Machinery (ACM) ,1998
- Stereo Matching with Nonlinear DiffusionInternational Journal of Computer Vision, 1998
- Spline-Based Image RegistrationInternational Journal of Computer Vision, 1997
- On the unification of line processes, outlier rejection, and robust statistics with applications in early visionInternational Journal of Computer Vision, 1996
- A stereo matching algorithm with an adaptive window: theory and experimentPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1994
- MPEGCommunications of the ACM, 1991
- Kalman filter-based algorithms for estimating depth from image sequencesInternational Journal of Computer Vision, 1989