Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint

  • Authors:

  • Joachim Weickert;Christoph Schnörr

  • Affiliations:

  • Computer Vision, Graphics, and Pattern Recognition Group, Department of Mathematics and Computer Science, University of Mannheim, 68131 Mannheim, Germany. Joachim.Weickert@uni-mannheim.de ...;Computer Vision, Graphics, and Pattern Recognition Group, Department of Mathematics and Computer Science, University of Mannheim, 68131 Mannheim, Germany. Christoph.Schnoerr@uni-mannheim. ...

  • Venue:
  • Journal of Mathematical Imaging and Vision
  • Year:
  • 2001

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Abstract

Nonquadratic variational regularization is a well-known and powerful approach for the discontinuity-preserving computation of optic flow. In the present paper, we consider an extension of flow-driven spatial smoothness terms to spatio-temporal regularizers. Our method leads to a rotationally invariant and time symmetric convex optimization problem. It has a unique minimum that can be found in a stable way by standard algorithms such as gradient descent. Since the convexity guarantees global convergence, the result does not depend on the flow initialization. Two iterative algorithms are presented that are not difficult to implement. Qualitative and quantitative results for synthetic and real-world scenes show that our spatio-temporal approach (i) improves optic flow fields significantly, (ii) smoothes out background noise efficiently, and (iii) preserves true motion boundaries. The computational costs are only 50% higher than for a pure spatial approach applied to all subsequent image pairs of the sequence.