Silhouette Area Based Similarity Measure for Template Matching in Constant Time

In this paper, we present a novel, fast, resolution-independent silhouette area-based matching approach. We approximate the silhouette area by a small set of axis-aligned rectangles. This yields a very memory efficient representation of templates. In addition, utilizing the integral image, we can thus compare a silhouette with an input image at an arbitrary position in constant time. Furthermore, we present a new method to build a template hierarchy optimized for our rectangular representation of template silhouettes. With the template hierarchy, the complexity of our matching method for n templates is O(log n). For example, we can match a hierarchy consisting of 1000 templates in 1.5ms. Overall, our contribution constitutes an important piece in the initialization stage of any tracker of (articulated) objects.

[1]  Franklin C. Crow,et al.  Summed-area tables for texture mapping , 1984, SIGGRAPH.

[2]  Hideo Saito,et al.  Human hand tracking from binocular image sequences , 1996, Proceedings of the 1996 IEEE IECON. 22nd International Conference on Industrial Electronics, Control, and Instrumentation.

[3]  Thomas S. Huang,et al.  Okapi-Chamfer matching for articulate object recognition , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[4]  Yoshiaki Shirai,et al.  3-D hand posture recognition by training contour variation , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[5]  Yen-Wei Chen,et al.  Articulated hand tracking by PCA-ICA approach , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

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

[7]  Thomas S. Huang,et al.  Tracking articulated hand motion with eigen dynamics analysis , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[8]  Björn Stenger,et al.  Model-based hand tracking using a hierarchical Bayesian filter , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Sartaj Sahni,et al.  Covering rectilinear polygons by rectangles , 1990, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[10]  Marco E. Lübbecke,et al.  Rectangle covers revisited computationally , 2005, WEA.

[11]  Joseph O'Rourke,et al.  Partitioning orthogonal polygons into fat rectangles in polynomial time , 2002, CCCG.

[12]  Michael I. Mandel,et al.  Visual Hand Tracking Using Nonparametric Belief Propagation , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[13]  Thomas Villmann,et al.  Batch and median neural gas , 2006, Neural Networks.

[14]  Ying Wu,et al.  Capturing natural hand articulation , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[15]  Ying Wu,et al.  3D model-based hand tracking using stochastic direct search method , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[16]  CipollaRoberto,et al.  Model-Based Hand Tracking Using a Hierarchical Bayesian Filter , 2006 .

[17]  Yoshiaki Shirai,et al.  Real-time 3D hand posture estimation based on 2D appearance retrieval using monocular camera , 2001, Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems.

[18]  Jimmy J. M. Tan,et al.  Minimum rectangular partition problem for simple rectilinear polygons , 1990, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[19]  V. S. Anil Kumar,et al.  Covering rectilinear polygons with axis-parallel rectangles , 1999, STOC '99.

[20]  Thomas Villmann,et al.  Batch neural gas , .

[21]  Hocine Ouhaddi,et al.  3D Hand Gesture Tracking by Model Registration , 1999 .

[22]  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.