Parametric reconstruction of generalized cylinders from limb edges

The three-dimensional (3-D) reconstruction of generalized cylinders (GCs) is an important research field in computer vision. One of the main difficulties is that some contour features in images cannot be reconstructed by traditional stereovision because they do not correspond to reflectance discontinuities of surface in space. In this paper, we present a novel, parametric approach for the 3-D reconstruction of circular generalized cylinders (CGCs) only from the limb edges of CGCs in two images. Instead of exploiting the invariant and quasiinvariant properties of some specific subclasses of GCs in projections, our reconstruction is achieved by some general assumptions on GCs, and can, therefore, be applied to a broader subclass of GCs. In order to improve robustness, we perform the extraction and labeling of the limb edge interactively, and estimate the epipolar geometry between two images by an optimal algorithm. Then, for different types of GCs, three kinds of symmetries (parallel symmetry, skew symmetry, and local smooth symmetry) are employed to compute the symmetry of limb edges. The surface points corresponding to limb edges in images are reconstructed by integrating the recovered epipolar geometry and the properties induced from the assumptions that we make on the GCs. Finally, a homography-based method is exploited to further refine the 3-D description of the GC with a coplanar curved axis.

[1]  Emanuele Trucco,et al.  Geometric Invariance in Computer Vision , 1995 .

[2]  M. Brady,et al.  Smoothed Local Symmetries and Their Implementation , 1984 .

[3]  Olivier D. Faugeras,et al.  The geometry of multiple images - the laws that govern the formation of multiple images of a scene and some of their applications , 2001 .

[4]  Terrance E. Boult,et al.  Recovery of SHGCs From a Single Intensity View , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Olivier D. Faugeras,et al.  Determining the fundamental matrix with planes: instability and new algorithms , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[6]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Ramakant Nevatia,et al.  Shape from Contour: Straight Homogeneous Generalized Cylinders and Constant Cross Section Generalized Cylinders , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  John E. Howland,et al.  Computer graphics , 1990, IEEE Potentials.

[9]  Les A. Piegl,et al.  The NURBS book (2nd ed.) , 1997 .

[10]  Takeo Kanade,et al.  Recovery of the Three-Dimensional Shape of an Object from a Single View , 1981, Artif. Intell..

[11]  Michel Dhome,et al.  Finding the Pose of an Object of Revolution , 1992, ECCV.

[12]  David J. Kriegman,et al.  On Recognizing and Positioning Curved 3-D Objects from Image Contours , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Andrew Blake,et al.  Surface shape from the deformation of apparent contours , 1992, International Journal of Computer Vision.

[14]  William A. Barrett,et al.  Intelligent scissors for image composition , 1995, SIGGRAPH.

[15]  Paulo R. S. Mendonça,et al.  Reconstruction of surfaces of revolution from single uncalibrated views , 2004, Image Vis. Comput..

[16]  Gérard G. Medioni,et al.  Full Volumetric Descriptions From Three Intensity Images , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  D FaugerasOlivier,et al.  Using Extremal Boundaries for 3-D Object Modeling , 1992 .

[18]  Gérard G. Medioni,et al.  Structural Indexing: Efficient 3-D Object Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Ramakant Nevatia,et al.  Recovering LSHGCs and SHGCs from stereo , 2004, International Journal of Computer Vision.

[20]  Gérard G. Medioni,et al.  Extraction Of Groups For Recognition , 1994, ECCV.

[21]  H. Opower Multiple view geometry in computer vision , 2002 .

[22]  Jean Ponce,et al.  Invariant Properties of Straight Homogeneous Generalized Cylinders and Their Contours , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Jerry L. Prince,et al.  An active contour model for mapping the cortex , 1995, IEEE Trans. Medical Imaging.

[24]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[25]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[26]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[27]  Philippe Saint-Marc,et al.  B-spline Contour Representation and Symmetry Detection , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Terrance E. Boult,et al.  Recovery of generalized cylinders from a single intensity image , 1990 .

[29]  Rachid Deriche,et al.  A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..

[30]  D. Kriegman,et al.  On recognizing and positioning curved 3D objects from image contours , 1989, [1989] Proceedings. Workshop on Interpretation of 3D Scenes.

[31]  Mi-Suen Lee,et al.  INFERRED DESCRIPTIONS IN TERMS OF CURVES, REGIONS AND JUNCTIONS FROM SPARSE, NOISY BINARY DATA , 1997 .

[32]  Gérard G. Medioni,et al.  Interactive 3D model extraction from a single image , 2001, Image Vis. Comput..

[33]  Ramakant Nevatia,et al.  Three-Dimensional Descriptions Based on the Analysis of the Invariant and Quasi-Invariant Properties of Some Curved-Axis Generalized Cylinders , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[34]  Gerald J. Agin Representation and description of curved objects , 1972 .