An Implicit Shape Model for Combined Object Categorization and Segmentation

We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior to recognition. However, in contrast to most standard approaches for object class recognition, our approach automatically segments the object as a result of the categorization.

[1]  Pietro Perona,et al.  Unsupervised Learning of Models for Recognition , 2000, ECCV.

[2]  Tomaso A. Poggio,et al.  Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Bernd Neumann,et al.  Computer Vision — ECCV’98 , 1998, Lecture Notes in Computer Science.

[4]  Tomaso A. Poggio,et al.  A Trainable System for Object Detection , 2000, International Journal of Computer Vision.

[5]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

[6]  Pietro Perona,et al.  Object class recognition by unsupervised scale-invariant learning , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[7]  Yizong Cheng,et al.  Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

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

[9]  S. Ullman Three-dimensional object recognition based on the combination of views , 1998, Cognition.

[10]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[11]  Cordelia Schmid,et al.  Constructing models for content-based image retrieval , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[12]  Bernt Schiele,et al.  Scale-Invariant Object Categorization Using a Scale-Adaptive Mean-Shift Search , 2004, DAGM-Symposium.

[13]  B. Schiele,et al.  Interleaved Object Categorization and Segmentation , 2003, BMVC.

[14]  Michael J. Jones,et al.  Model-Based Matching by Linear Combinations of Prototypes , 1996 .

[15]  Jianbo Shi,et al.  Object-Specific Figure-Ground Segregation , 2003, CVPR.

[16]  Dan Roth,et al.  Learning a Sparse Representation for Object Detection , 2002, ECCV.

[17]  Takeo Kanade,et al.  A statistical method for 3D object detection applied to faces and cars , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[18]  Pietro Perona,et al.  A Probabilistic Approach to Object Recognition Using Local Photometry and Global Geometry , 1998, ECCV.

[19]  Thomas S. Huang,et al.  Fusion of global and local information for object detection , 2002, Object recognition supported by user interaction for service robots.

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

[21]  B. Schiele,et al.  Combined Object Categorization and Segmentation With an Implicit Shape Model , 2004 .

[22]  Alan L. Yuille,et al.  Feature extraction from faces using deformable templates , 2004, International Journal of Computer Vision.

[23]  Ruzena Bajcsy,et al.  Segmentation of range images as the search for geometric parametric models , 1995, International Journal of Computer Vision.

[24]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[25]  Mads Nielsen,et al.  Computer Vision — ECCV 2002 , 2002, Lecture Notes in Computer Science.

[26]  Bernt Schiele,et al.  Pedestrian detection in crowded scenes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[27]  Derek R. Magee,et al.  Detecting lameness using 'Re-sampling Condensation' and 'multi-stream cyclic hidden Markov models' , 2002, Image Vis. Comput..

[28]  Christopher M. Bishop,et al.  Non-linear Bayesian Image Modelling , 2000, ECCV.

[29]  Shimon Ullman,et al.  Class-Specific, Top-Down Segmentation , 2002, ECCV.