An Image Oriented CAD Approach

Matching abstract CAD models with images is a well studied problem. It includes the problems of identifying modelled objects for which 3D CAD data is available in images, and of locating them with respect to a given reference frame. Some authors have concluded that this problem has no real general solution as the representation levels are too different (see for instance the discussion in the workshop of CAD model-based vision [Bow91]).

[1]  J J Koenderink,et al.  What Does the Occluding Contour Tell Us about Solid Shape? , 1984, Perception.

[2]  O. D. Faugeras,et al.  Camera Self-Calibration: Theory and Experiments , 1992, ECCV.

[3]  Joseph L. Mundy,et al.  Projective geometry for machine vision , 1992 .

[4]  Radu Horaud,et al.  Finding Geometric and Relational Structures in an Image , 1990, ECCV.

[5]  David W. Jacobs,et al.  Model group indexing for recognition , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  William Rucklidge,et al.  Locating objects using the Hausdorff distance , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  C. Schmid,et al.  Matching by local invariants , 1995 .

[8]  J.B. Burns,et al.  View Variation of Point-Set and Line-Segment Features , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Shimon Ullman,et al.  Limitations of Non Model-Based Recognition Schemes , 1992, ECCV.

[10]  Hans-Hellmut Nagel,et al.  3D pose estimation by fitting image gradients directly to polyhedral models , 1995, Proceedings of IEEE International Conference on Computer Vision.

[11]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[12]  Cordelia Schmid,et al.  Combining greyvalue invariants with local constraints for object recognition , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Takeo Kanade,et al.  Applying Sensor Models To Automatic Generation Of Object Recognition Programs , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[14]  Chien-Huei Chen,et al.  CAD-based feature-utility measures for automatic vision programming , 1991, [1991 Proceedings] Workshop on Directions in Automated CAD-Based Vision.

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

[16]  Jezekiel Ben-Arie The Probabilistic Peaking Effect of Viewed Angles and Distances with Application to 3-D Object Recognition , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Jin-Long Chen,et al.  Matching curved 3D object models to 2D images , 1994, Proceedings of 1994 IEEE 2nd CAD-Based Vision Workshop.

[18]  Robert C. Bolles,et al.  3DPO: A Three- Dimensional Part Orientation System , 1986, IJCAI.

[19]  Sven J. Dickinson,et al.  The Use of Geons for Generic 3D Object Recognition , 1993, IJCAI.

[20]  Olivier D. Faugeras,et al.  On the geometry and algebra of the point and line correspondences between N images , 1995, Proceedings of IEEE International Conference on Computer Vision.

[21]  M K Brown,et al.  The Extraction of Curved Surface Features with Generic Range Sensors , 1986 .

[22]  Juneho Yi,et al.  Rapid object recognition from a large model database , 1994, Proceedings of 1994 IEEE 2nd CAD-Based Vision Workshop.

[23]  Olaf Kübler,et al.  Simulation of neural contour mechanisms: from simple to end-stopped cells , 1992, Vision Research.

[24]  Sang Wook Lee,et al.  Detection of specularity using colour and multiple views , 1992, Image Vis. Comput..

[25]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  David G. Lowe,et al.  Three-Dimensional Object Recognition from Single Two-Dimensional Images , 1987, Artif. Intell..

[27]  Alex Pentland,et al.  Why aspect graphs are not (yet) practical for computer vision , 1991, [1991 Proceedings] Workshop on Directions in Automated CAD-Based Vision.

[28]  Patrick Gros,et al.  Using Quasi-Invariants for Automatic Model Building and Object Recognition: an Overview , 1994, Object Representation in Computer Vision.

[29]  Bart M. ter Haar Romeny,et al.  Geometry-Driven Diffusion in Computer Vision , 1994, Computational Imaging and Vision.

[30]  Raimund Seidel,et al.  Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[32]  Patrick Gros,et al.  Matching and Clustering: Two Steps Toward Automatic Object Modeling in Computer Vision , 1995, Int. J. Robotics Res..

[33]  Patrick Gros,et al.  Rapid Object Indexing and Recognition Using Enhanced Geometric Hashing , 1996, ECCV.

[34]  Amnon Shashua,et al.  Trilinearity in Visual Recognition by Alignment , 1994, ECCV.

[35]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

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

[37]  Andrew P. Witkin,et al.  Scale-Space Filtering , 1983, IJCAI.

[38]  Alan L. Yuille,et al.  FORMS: A flexible object recognition and modelling system , 1995, Proceedings of IEEE International Conference on Computer Vision.