Mathematical properties of the two-dimensional motion field: from singular points to motion parameters

The motion field, that is, the two-dimensional vector field associated with the velocity of points on the image plane, can be seen as the flow vector of the solution to a planar system of differential equations. Therefore the theory of planar dynamical systems can be used to understand qualitative and quantitative properties of motion. In this paper it is shown that singular points of the motion field, which are the points where the field vanishes, and the time evolution of their local structure capture essential features of three-dimensional motion that make it possible to distinguish translation, rotation, and general motion and also make possible the computation of the relevant motion parameters. Singular points of the motion field are the perspective projection onto the image plane of the intersection between a curve called the characteristic curve, which depends on only motion parameters, and the surface of the moving object. In most cases, singular points of the motion field are left unchanged in location and spatial structure by small perturbations affecting the vector field. Therefore a description of motion based on singular points can be used even when the motion field of an image sequence has not been estimated with high accuracy.

[1]  J. Gibson The perception of the visual world , 1951 .

[2]  M. Peixoto,et al.  Structural stability on two-dimensional manifolds☆ , 1962 .

[3]  Claude L. Fennema,et al.  Velocity determination in scenes containing several moving objects , 1979 .

[4]  S. Ullman,et al.  The interpretation of visual motion , 1977 .

[5]  H. C. Longuet-Higgins,et al.  The interpretation of a moving retinal image , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[6]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[7]  Hans-Hellmut Nagel,et al.  Volumetric model and 3D trajectory of a moving car derived from monocular TV frame sequences of a street scene , 1981, Comput. Graph. Image Process..

[8]  H. Nagel,et al.  On the Selection of Critical Points and Local Curvature Extrema of Region Boundaries for Interframe Matching , 1983 .

[9]  R. Haralick,et al.  The Facet Approach to Optic Flow , 1983 .

[10]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[11]  S. Ullman Recent Computational Studies in the Interpretation of Structure from Motion , 1983 .

[12]  Thomas S. Huang,et al.  Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  E. Hildreth The computation of the velocity field , 1984, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[14]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[15]  Kenichi Kanatani Structure from Motion Without Correspondence: General Principle , 1985, IJCAI.

[16]  Hans-Hellmut Nagel,et al.  An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Hans-Hellmut Nagel,et al.  Toward the derivation of three-dimensional descriptions from image sequences for nonconvex moving objects , 1986, Comput. Vis. Graph. Image Process..

[18]  Federico Girosi,et al.  On The Understanding Of Motion Of Rigid Objects , 1987, Other Conferences.

[19]  A. Waxman An image flow paradigm , 1987 .

[20]  David J. Heeger,et al.  Optical flow from spatialtemporal filters , 1987 .

[21]  Alessandro Verri,et al.  Against Quantitative Optical Flow , 1987 .

[22]  D. Shulman,et al.  (Non-)rigid motion interpretation : a regularized approach , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[23]  Wilfried Enkelmann,et al.  Investigations of multigrid algorithms for the estimation of optical flow fields in image sequences , 1988, Comput. Vis. Graph. Image Process..

[24]  Hans-Hellmut Nagel,et al.  Image Sequences - Ten (Octal) Years - from phenomenology towards a Theoretical Foundation , 1988, Int. J. Pattern Recognit. Artif. Intell..