Intelligent Techniques For Character Animation

Due to the popularity of optical motion capture system, more and more realistichuman motion data can be acquired easily. In recent years, large and highly detailedhuman motion database is commercially available and widely used in variousapplications such as video games, animation films, sports simulation and virtualreality. Therefore, many researchers have been focused on how to edit, manipulate,reuse the existing motion data, and develop new techniques for producing humananimation automatically and intelligently.The work of this thesis is to explore automatic and intelligent method for analyzing,managing and reusing motion capture data, and try to develop some automatic andintelligent approaches to produce 3D human animations efficiently. This thesispresents the following algorithms, including automatic motion segmentation,keyframe extraction from human motion sequence, motion retrieval based onkeyframes, automatic synthesis and editing of motion styles, a script engine forrealistic human movement generation based on MoCap data, and automatic humanmovement generation based on motion programming.A novel method was proposed to get primitive actions from long MoCap sequenceefficiently. Original motion sequences lie on a high-dimensional manifold which ishighly folded and twisted, so it is difficult to cluster the similar poses together to formdistinct primitive actions. Here we use a non-linear dimensionality reductiontechnique to map original motion sequences into low-dimensional manifold, and thenclustering techniques are applied to segment primitive actions apart.We propose a keyframe extraction method based on a novel layered curvesimplification algorithm for motion capture data. Bone angles are employed as motionfeatures and keyframe candidates can be selected based on them. After that, thelayered curve simplification algorithm will be used to refine those candidates and thekeyframe collection can be gained. The experiments demonstrate that our method cannot only compress and summarize the motion capture data efficiently, but also keepthe consistency of keyframe collection between similar human motion sequences,which is of great benefit to further motion data retrieval or editing.Chapter 5 introduces a novel motion retrieval approach based on keyframes. Whenmotion retrieval command is issued, the distance matrix is constructed betweenkeyframe set of query example and that of a motion from database. Then thesimilarity between them is calculated based on this distance matrix. Comparing tomost existing content-based motion retrieval approaches our method possesses bettertime efficiency performance without dependence on the precomputed indexingstructure and preset parameters, which is a preference for the incremental motiondatabase.We propose a framework for automatic, real-time and quantitative synthesis andediting of human motion styles. In this framework Principle Component Analysistheory is used to map original styled human motions into subspaces, which can reduce computational complexity while reserving the intrinsic properties of original data.Synthesis and editing methods are applied in such subspaces and then motions withnew styles can be reconstructed. As realistic human motions may have multiple styles,we also present a novel method to synthesize and edit motions with multiple styles.Chapter 7 proposes a script engine framework for realistic human movementgeneration based on well-organized MoCap database. Users can make or edit motionscripts which describe the human movement type, order, and details. Then the scriptsequence are decomposed into sequential commands which are used to retrieve propermotion clips from MoCap database and generate final movement sequence.Furthermore, users can define their own motion elements table and scripts in thisflexible script engine framework according to various MoCap data sets. Theexperiment result shows that this script engine framework can achieve goodperformance and can be used as human motion engine in various applications, such ascomputer game, animation production, sports simulation and virtual reality.Chapter 8 proposes a framework to program the movements of characters andgenerate navigation animations in virtual environment. Given a virtual environment, avisual user interface is provided for animators to interactively generate motion scripts,describing the characters' movements in this scene and finally used to retrieve motionclips from MoCap database and generate navigation animations automatically. Thisframework also provides flexible mechanism for animators to get varied resultinganimations by configurable table of motion bias coefficients and interactive visualuser interface.In chapter 9, we give a conclusion of this thesis and discuss the future work.