Superquadrics for Segmenting and Modeling Range Data

We present an approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g. in terms of surfaces). The approach is based on the recover-and-select paradigm. We present several experiments on real and synthetic range images, where we demonstrate the stability of the results with respect to viewpoint and noise.

[1]  Dimitris N. Metaxas,et al.  Dynamic 3D models with local and global deformations: deformable superquadrics , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[2]  Robert Bergevin,et al.  Extraction of line drawing features for object recognition , 1992, Pattern Recognit..

[3]  Pascal Fua,et al.  Objective Functions for Feature Discrimination , 1989, IJCAI.

[4]  Barr,et al.  Superquadrics and Angle-Preserving Transformations , 1981, IEEE Computer Graphics and Applications.

[5]  Franc Solina,et al.  Segmentor : an object -oriented framework for image segmentation , 1996 .

[6]  Frank P. Ferrie,et al.  Darboux Frames, Snakes, and Super-Quadrics: Geometry from the Bottom Up , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Ramakant Nevatia,et al.  Using Perceptual Organization to Extract 3-D Structures , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Tin-Lup Wong,et al.  Solid modeling of kinematic chains , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[9]  Ruzena Bajcsy,et al.  Volumetric segmentation of range images of 3D objects using superquadric models , 1993 .

[10]  Alan H. Barr,et al.  Global and local deformations of solid primitives , 1984, SIGGRAPH.

[11]  Frank P. Ferrie,et al.  From uncertainty to visual exploration , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[12]  Christof Koch,et al.  Selecting One Among the Many: A Simple Network Implementing Shifts in Selective Visual Attention , 1984 .

[13]  Anil K. Jain,et al.  Recognizing geons from superquadrics fitted to range data , 1992, Image Vis. Comput..

[14]  Ruzena Bajcsy,et al.  Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Alex Pentland,et al.  Perceptual Organization and the Representation of Natural Form , 1986, Artif. Intell..

[16]  Alex Pentland,et al.  Closed-form solutions for physically-based shape modeling and recognition , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[17]  Hervé Delingette,et al.  A perception and Manipulation System for collecting rock samples , 1991 .

[18]  Franc Solina,et al.  Selective scene modeling , 1992, [1992] Proceedings. 11th IAPR International Conference on Pattern Recognition.

[19]  R. Nevatia,et al.  Perceptual Organization for Scene Segmentation and Description , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Pradeep K. Khosla,et al.  Manipulator control with superquadric artificial potential functions: theory and experiments , 1990, IEEE Trans. Syst. Man Cybern..

[21]  Ruzena Bajcsy,et al.  Finding Parametric Curves in an Image , 1992, ECCV.

[22]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[23]  Xin Chen,et al.  Vision-based construction of CAD models from range images , 1993, 1993 (4th) International Conference on Computer Vision.

[24]  Peter K. Allen,et al.  Acquisition and interpretation of 3-D sensor data from touch , 1990, IEEE Trans. Robotics Autom..

[25]  David G. Lowe,et al.  Perceptual Organization and Visual Recognition , 2012 .

[26]  Alex Pentland,et al.  Part Segmentation for Object Recognition , 1989, Neural Computation.

[27]  Paul J. Besl,et al.  Surfaces in Range Image Understanding , 1988, Springer Series in Perception Engineering.

[28]  Andrzej Cichocki,et al.  Neural networks for optimization and signal processing , 1993 .

[29]  Irving Biederman,et al.  Human image understanding: Recent research and a theory , 1985, Comput. Vis. Graph. Image Process..

[30]  A. Pentland.  Recognition by Parts , 1987 .

[31]  Ruzena Bajcsy,et al.  Segmentation versus object representation—are they separable? , 1989 .

[32]  Alex Pentland,et al.  Cooperative Robust Estimation Using Layers of Support , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Ruzena Bajcsy,et al.  Segmentation as the search for the best description of the image in terms of primitives , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[34]  Dimitris N. Metaxas,et al.  Shape and Nonrigid Motion Estimation Through Physics-Based Synthesis , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Donald D. Hoffman,et al.  Parts of recognition , 1984, Cognition.

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

[37]  Jean Ponce,et al.  Describing surfaces , 1985, Comput. Vis. Graph. Image Process..