Real-time nonrigid surface detection

We present a real-time method for detecting deformable surfaces, with no need whatsoever for a priori pose knowledge. Our method starts from a set of wide baseline point matches between an undeformed image of the object and the image in which it is to be detected. The matches are used not only to detect but also to compute a precise mapping from one to the other. The algorithm is robust to large deformations, lighting changes, motion blur, and occlusions. It runs at 10 frames per second on a 2.8 GHz PC and we are not aware of any other published technique that produces similar results. Combining deformable meshes with a well designed robust estimator is key to dealing with the large number of parameters involved in modeling deformable surfaces and rejecting erroneous matches for error rates of up to 95%, which is considerably more than what is required in practice.

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

[2]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[3]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Pascal Fua,et al.  Model-Based Optimization: An Approach to Fast, Accurate, and Consistent Site Modeling from Imagery , 1997 .

[5]  Dimitris N. Metaxas,et al.  Deformable model-based shape and motion analysis from images using motion residual error , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  Luc Van Gool,et al.  Recognizing color patterns irrespective of viewpoint and illumination , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[7]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[8]  Michel Dhome,et al.  Recognition of 3D textured objects by mixing view-based and model-based representations , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[9]  Adam Baumberg,et al.  Reliable feature matching across widely separated views , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[10]  Luc Van Gool,et al.  Wide Baseline Stereo Matching based on Local, Affinely Invariant Regions , 2000, BMVC.

[11]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[12]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Cordelia Schmid,et al.  An Affine Invariant Interest Point Detector , 2002, ECCV.

[14]  Xavier Pennec,et al.  Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration , 2002, ECCV.

[15]  Vincent Lepetit,et al.  Fully automated and stable registration for augmented reality applications , 2003, The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings..

[16]  Anand Rangarajan,et al.  A new point matching algorithm for non-rigid registration , 2003, Comput. Vis. Image Underst..

[17]  Vincent Lepetit,et al.  Stable real-time 3D tracking using online and offline information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Adrien Bartoli,et al.  Direct Estimation of Non-Rigid Registration , 2004, BMVC.

[19]  P. Fua,et al.  Towards Recognizing Feature Points using Classification Trees , 2004 .

[20]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[21]  Radu Horaud,et al.  Point Trajectories and a Smooth Surface Model , 2004, European Conference on Computer Vision.

[22]  Larry S. Davis,et al.  Structure of Applicable Surfaces from Single Views , 2004, ECCV.

[23]  Simon Baker Real-time non-rigid driver head tracking for driver mental state estimation , 2004 .

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

[25]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[26]  Vincent Lepetit,et al.  Point matching as a classification problem for fast and robust object pose estimation , 2004, CVPR 2004.

[27]  Luc Van Gool,et al.  Simultaneous Object Recognition and Segmentation by Image Exploration , 2004, ECCV.

[28]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Pascal Fua,et al.  Object-centered surface reconstruction: Combining multi-image stereo and shading , 1995, International Journal of Computer Vision.

[30]  Vincent Lepetit,et al.  Randomized trees for real-time keypoint recognition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).