Hybrid compression of dynamic 3D mesh data

Geometric representation of objects and surfaces in terms of 3D meshes is becoming increasingly important in a variety of applications. As the amount of data in this format increases, the problem of compression becomes vital for the further development of the field. In this paper we present a codec for dynamic 3D mesh data that utilizes the “hybrid” framework from video coding, built upon temporal prediction and spatial transform. We discuss various features of the codec, including unrestricted quantization and two-stage entropy coding, and investigate its compression efficiency on a variety of test material. A discussion of various prediction structures and their impact on error resilience is also provided.

[1]  Ivan V. Bajic,et al.  A two-stage H.264/AVC encoder for video streaming with fast reference picture selection , 2008, WMuNeP '08.

[2]  Gene Cheung,et al.  Reference Frame Optimization for Multiple-Path Video Streaming With Complexity Scaling , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Jörn Ostermann,et al.  Connectivity-Guided Predictive Compression of Dynamic 3D Meshes , 2006, 2006 International Conference on Image Processing.

[4]  Jörn Ostermann,et al.  Spatially and temporally scalable compression of animated 3D meshes with MPEG-4 / FAMC , 2008, 2008 15th IEEE International Conference on Image Processing.

[5]  James D. K. Kim,et al.  Interpolator data compression for MPEG-4 animation , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[6]  A F Ayoub,et al.  Applications of 3D Imaging in Orthodontics: Part II , 2004, Journal of orthodontics.

[7]  Peter Eisert,et al.  Rate-distortion-optimized predictive compression of dynamic 3D mesh sequences , 2006, Signal Process. Image Commun..

[8]  Wolfgang Straßer,et al.  Predictive-DCT Coding for 3D Mesh Sequences Compression , 2008, J. Virtual Real. Broadcast..

[9]  Hans-Peter Seidel,et al.  Motion capture using joint skeleton tracking and surface estimation , 2009, CVPR.

[10]  Markus Flierl,et al.  Low-latency video transmission over lossy packet networks using rate-distortion optimized reference picture selection , 2002, Proceedings. International Conference on Image Processing.

[11]  Jinghua Zhang,et al.  Octree-based animated geometry compression , 2007, Comput. Graph..

[12]  Ivan V. Bajic,et al.  MoCap data coding with unrestricted quantization and rate control , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  Titus B. Zaharia,et al.  FAMC: The MPEG-4 standard for Animated Mesh Compression , 2008, 2008 15th IEEE International Conference on Image Processing.

[14]  L. Vasa,et al.  CODDYAC: Connectivity Driven Dynamic Mesh Compression , 2007, 2007 3DTV Conference.

[15]  Ralf Sarlette,et al.  Simple and efficient compression of animation sequences , 2005, SCA '05.

[16]  Craig Gotsman,et al.  Compression of soft-body animation sequences , 2004, Comput. Graph..

[17]  Ivan V. Bajic,et al.  Error concealment strategies for Motion Capture data streaming , 2011, 2011 IEEE International Conference on Multimedia and Expo.

[18]  Jarek Rossignac,et al.  Edgebreaker: Connectivity Compression for Triangle Meshes , 1999, IEEE Trans. Vis. Comput. Graph..

[19]  Marc Alexa,et al.  Representing Animations by Principal Components , 2000, Comput. Graph. Forum.

[20]  Nasir D. Memon Adaptive coding of DCT coefficients by Golomb-Rice codes , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).