TEMPORAL 3 D SHAPE MATCHING

This paper introduces a novel 4D shape descriptor to match temporal surface sequences. A quantitative evaluation based on the Receiver-Operator Characteristic (ROC) curve is presented to compare the performance of conventional 3D shape descriptors with and without using a time filter. Featurebased 3D Shape Descriptors including Shape Distribution [24], Spin Image [14], Shape Histogram [1] and Spherical Harmonics [16] are considered. Evaluation shows that filtered descriptors outperform unfiltered descriptors and the best performing volume-sampling shape-histogram descriptor is extended to define a new 4D “shape-flow” descriptor. Shape-flow matching demonstrates improved performance in the context of matching time-varying sequences which is motivated by the requirement to connect similar sequences for animation production. Both simulated and real 3D human surface motion sequences are used for evaluation.

[1]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Jitendra Malik,et al.  Recognizing action at a distance , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[3]  Marcel Körtgen,et al.  3D Shape Matching with 3D Shape Contexts , 2003 .

[4]  Ronen Basri,et al.  Actions as space-time shapes , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[5]  James W. Davis,et al.  The Recognition of Human Movement Using Temporal Templates , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Thomas A. Funkhouser,et al.  Shape-based retrieval and analysis of 3d models , 2005, CACM.

[7]  Cordelia Schmid,et al.  IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2004, Washington, DC, USA, June 27 - July 2, 2004 , 2004, CVPR Workshops.

[8]  Adrian Hilton,et al.  A Study of Shape Similarity for Temporal Surface Sequences of People , 2007, Sixth International Conference on 3-D Digital Imaging and Modeling (3DIM 2007).

[9]  Roddy MacLeod,et al.  Coarse Filters for Shape Matching , 2002, IEEE Computer Graphics and Applications.

[10]  Lisa Gralewski,et al.  Theory and Practice of Computer Graphics , 2004 .

[11]  A. Hilton,et al.  A Quantitative Comparison Study of Shape Similarity for Temporal Surface Sequences of People , 2007 .

[12]  Martial Hebert,et al.  On 3D shape similarity , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Yiannis Aloimonos,et al.  Animated Heads: From 3D Motion Fields to Action Descriptions , 2000, DEFORM/AVATARS.

[14]  Bernard Chazelle,et al.  Shape distributions , 2002, TOGS.

[15]  Ryutarou Ohbuchi,et al.  Shape-similarity search of 3D models by using enhanced shape functions , 2005, Int. J. Comput. Appl. Technol..

[16]  Bülent Sankur,et al.  Transform-based methods for indexing and retrieval of 3D objects , 2005, Fifth International Conference on 3-D Digital Imaging and Modeling (3DIM'05).

[17]  Kiyoharu Aizawa,et al.  Motion Editing in 3D Video Database , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[18]  Richard Szeliski,et al.  Video textures , 2000, SIGGRAPH.

[19]  Remco C. Veltkamp,et al.  A Survey of Content Based 3D Shape Retrieval Methods , 2004, SMI.

[20]  Adrian Hilton,et al.  Video-based character animation , 2005, SCA '05.

[21]  Adrian Hilton,et al.  Surface Capture for Performance-Based Animation , 2007, IEEE Computer Graphics and Applications.

[22]  Daniel A. Keim,et al.  Content-Based 3D Object Retrieval , 2007, IEEE Computer Graphics and Applications.

[23]  Chin Seng Chua,et al.  Point Signatures: A New Representation for 3D Object Recognition , 1997, International Journal of Computer Vision.

[24]  Hans-Peter Kriegel,et al.  3D Shape Histograms for Similarity Search and Classification in Spatial Databases , 1999, SSD.

[25]  Atilla Baskurt,et al.  ART extension for description, indexing and retrieval of 3D objects , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[26]  Marcin Novotni,et al.  3D zernike descriptors for content based shape retrieval , 2003, SM '03.

[27]  Raphaëlle Chaine,et al.  Direct Spherical Harmonic Transform of a Triangulated Mesh , 2006, J. Graph. Tools.

[28]  Karthik Ramani,et al.  Three-dimensional shape searching: state-of-the-art review and future trends , 2005, Comput. Aided Des..

[29]  BENJAMIN BUSTOS,et al.  Feature-based similarity search in 3D object databases , 2005, CSUR.

[30]  HebertMartial,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999 .

[31]  Tsuhan Chen,et al.  Efficient feature extraction for 2D/3D objects in mesh representation , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[32]  Xavier Binefa,et al.  Robust Real-Time Periodic Motion Detection, Analysis, and Applications , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Dietmar Saupe,et al.  3D Shape Descriptor Based on 3D Fourier Transform , 2001 .

[34]  Szymon Rusinkiewicz,et al.  Rotation Invariant Spherical Harmonic Representation of 3D Shape Descriptors , 2003, Symposium on Geometry Processing.

[35]  Bernard Chazelle,et al.  A Reflective Symmetry Descriptor , 2002, ECCV.

[36]  Marc Rioux,et al.  Description of shape information for 2-D and 3-D objects , 2000, Signal Process. Image Commun..

[37]  Jitendra Malik,et al.  Shape Context: A New Descriptor for Shape Matching and Object Recognition , 2000, NIPS.

[38]  Rémi Ronfard,et al.  Motion History Volumes for Free Viewpoint Action Recognition , 2005 .