Fast Cost-Volume Filtering for Visual Correspondence and Beyond

Many computer vision tasks can be formulated as labeling problems. The desired solution is often a spatially smooth labeling where label transitions are aligned with color edges of the input image. We show that such solutions can be efficiently achieved by smoothing the label costs with a very fast edge preserving filter. In this paper we propose a generic and simple framework comprising three steps: (i) constructing a cost volume (ii) fast cost volume filtering and (iii) winner-take-all label selection. Our main contribution is to show that with such a simple framework state-of-theart results can be achieved for several computer vision applications. In particular, we achieve (i) disparity maps in real-time, whose quality exceeds those of all other fast (local) approaches on the Middlebury stereo benchmark, and (ii) optical flow fields with very fine structures as well as large displacements. To demonstrate robustness, the few parameters of our framework are set to nearly identi...

• Type: Journal
• Year: 2011
• Where: CVPR
• Authors: Christoph Rhemann, Asmaa Hosni, Michael Bleyer, Carsten Rother, margrit Gelautz
• Keywords: Computer Vision, CVPR 2011, Simple Framework, Simple Framework State-of-theart, Winner-take-all Label Selection