Temporally consistent disparity and optical flow via efficient spatio-temporal filtering
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Practical temporal consistency for image-based graphics applications
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm
Computer Graphics Forum
Consistent stylization and painterly rendering of stereoscopic 3D images
NPAR '12 Proceedings of the Symposium on Non-Photorealistic Animation and Rendering
Stereoscopic line drawing using depth maps
ACM SIGGRAPH 2012 Posters
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Filter-Based mean-field inference for random fields with higher-order terms and product label-spaces
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Continuous markov random fields for robust stereo estimation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
A locally linear regression model for boundary preserving regularization in stereo matching
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Extracting 3d scene-consistent object proposals and depth from stereo images
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
An improved stereo matching algorithm with ground plane and temporal smoothness constraints
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
OmniKinect: real-time dense volumetric data acquisition and applications
Proceedings of the 18th ACM symposium on Virtual reality software and technology
Secrets of adaptive support weight techniques for local stereo matching
Computer Vision and Image Understanding
Scene reconstruction from high spatio-angular resolution light fields
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
Cross anisotropic cost volume filtering for segmentation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Adaptive integration of feature matches into variational optical flow methods
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Special Section on Expressive Graphics: Stereoscopic 3D image stylization
Computers and Graphics
Adaptive large window correlation for optical flow estimation with discrete optimization
Image and Vision Computing
Information permeability for stereo matching
Image Communication
Cost volume-based interactive depth editing in stereo post-processing
Proceedings of the 10th European Conference on Visual Media Production
Random walks in directed hypergraphs and application to semi-supervised image segmentation
Computer Vision and Image Understanding
Stereo matching by using the global edge constraint
Neurocomputing
International Journal of Computer Vision
Fast stereo matching using adaptive guided filtering
Image and Vision Computing
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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-the-art 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 identical values for both applications. Also, competitive results for interactive image segmentation are presented. With this work, we hope to inspire other researchers to leverage this framework to other application areas.