Paper Info
Title
Enhancing Spatial Keyframe Animations With Motion Capture
Abstract
While motion capture (mocap) achieves realistic character animation at great cost, keyframing is capable of producing less realistic but more controllable animations. In this paper we show how to combine the Spatial Keyframing Framework (SKF) of Igarashi et al.(Igarashi et al., 2005) and multidimensional projection techniques to reuse mocap data in several ways. For instance, by extracting meaningful poses and projecting them on a plane, it is possible to sketch new animations using the SKF. Additionally, we show that multidimensional projection also can be used for visualization and motion analysis. We also propose a method for mocap compaction with the help of SK's pose reconstruction (backprojection) algorithm. This compaction scheme was implemented for several known projection schemes and empirically tested alongside traditional temporal decimation schemes. Finally, we present a novel multidimensional projection optimization technique that significantly enhances SK-based compaction and can also be applied to other contexts where a back-projection algorithm is available.
Year
DOI
Venue
2019
10.5220/0007296800310040
PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (GRAPP), VOL 1
Keywords
Field
DocType
Motion Capture, Keyframing, Spatial Keyframe, Dimension Reduction, Multidimensional Projection
Motion capture,Computer vision,Dimensionality reduction,Decimation,Computer graphics (images),Computer science,Visualization,Reuse,Character animation,Artificial intelligence,Motion analysis,Sketch
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Bernardo Costa100.68
Claudio Esperança2134.79