Matrix computations (3rd ed.)
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Dimension reduction by local principal component analysis
Neural Computation
Compression of time-dependent geometry
I3D '99 Proceedings of the 1999 symposium on Interactive 3D graphics
Temporal and spatial level of details for dynamic meshes
VRST '01 Proceedings of the ACM symposium on Virtual reality software and technology
Incremental Singular Value Decomposition of Uncertain Data with Missing Values
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Dynapack: space-time compression of the 3D animations of triangle meshes with fixed connectivity
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Geometry videos: a new representation for 3D animations
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
3D Compression Made Simple: Edgebreaker with Zip&Wrap on a Corner-Table
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
PCA-Based Walking Engine Using Motion Capture Data
CGI '04 Proceedings of the Computer Graphics International
Wavelet compression of parametrically coherent mesh sequences
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Meshless deformations based on shape matching
ACM SIGGRAPH 2005 Papers
Simple and efficient compression of animation sequences
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Mesh decomposition using motion information from animation sequences: Animating Geometrical Models
Computer Animation and Virtual Worlds - CASA 2005
Curvature estimation of point-sampled surfaces and its applications
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III
Interpolator data compression for MPEG-4 animation
IEEE Transactions on Circuits and Systems for Video Technology
Shape-based simplification for 3d animation models using shape operator sequences
CIT'10 Proceedings of the 4th international conference on Communications and information technology
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This paper investigates the use of the affine transformation matrix when employing principal component analysis (PCA) to compress the data of 3D animation models. Satisfactory results were achieved for the common 3D models by using PCA because it can simplify several related variables to a few independent main factors, in addition to making the animation identical to the original by using linear combinations. The selection of the principal component factor (also known as the base) is still a subject for further research. Selecting a large number of bases could improve the precision of the animation and reduce distortion for a large data volume. Hence, a formula is required for base selection. This study develops an automatic PCA selection method, which includes the selection of suitable bases and a PCA separately on the three axes to select the number of suitable bases for each axis. PCA is more suitable for animation models for apparent stationary movement. If the original animation model is integrated with transformation movements such as translation, rotation, and scaling (RTS), the resulting animation model will have a greater distortion in the case of the same base vector with regard to apparent stationary movement. This paper is the first to extract the model movement characteristics using the affine transformation matrix and then to compress 3D animation using PCA. The affine transformation matrix can record the changes in the geometric transformation by using 4 × 4 matrices. The transformed model can eliminate the influences of geometric transformations with the animation model normalized to a limited space. Subsequently, by using PCA, the most suitable base vector (variance) can be selected more precisely.