Binocular Image Flows: Steps Toward Stereo-Motion Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovery of Nonrigid Motion and Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based joint motion and structure estimation from stereo images
Computer Vision and Image Understanding
The reconstruction of dynamic 3D structure of biological objects using stereo microscope images
Machine Vision and Applications
A Multibody Factorization Method for Independently Moving Objects
International Journal of Computer Vision
Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Real-time joint disparity and disparity flow estimation on programmable graphics hardware
Computer Vision and Image Understanding
Range Flow for Varying Illumination
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A globally optimal approach for 3D elastic motion estimation from stereo sequences
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Go with the flow: hand trajectories in 3d via clustered scene flow
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
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Scene flow methods estimate the three-dimensional motion field for points in the world, using multi-camera video data. Such methods combine multi-view reconstruction with motion estimation approaches. This paper describes an alternative formulation for dense scene flow estimation that provides convincing results using only two cameras by fusing stereo and optical flow estimation into a single coherent framework. To handle the aperture problems inherent in the estimation task, a multi-scale method along with a novel adaptive smoothing technique is used to gain a regularized solution. This combined approach both preserves discontinuities and prevents over-regularization - two problems commonly associated with basic multi-scale approaches. Internally, the framework generates probability distributions for optical flow and disparity. Taking into account the uncertainty in the intermediate stages allows for more reliable estimation of the 3D scene flow than standard stereo and optical flow methods allow. Experiments with synthetic and real test data demonstrate the effectiveness of the approach.