Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Motion texture: a two-level statistical model for character motion synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive motion generation from examples
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
FootSee: an interactive animation system
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Performance animation from low-dimensional control signals
ACM SIGGRAPH 2005 Papers
Dynamic response for motion capture animation
ACM SIGGRAPH 2005 Papers
Style translation for human motion
ACM SIGGRAPH 2005 Papers
An Efficient Technique for Mining Usage Profiles Using Relational Fuzzy Subtractive Clustering
WIRI '05 Proceedings of the International Workshop on Challenges in Web Information Retrieval and Integration
A 3-dimensional sift descriptor and its application to action recognition
Proceedings of the 15th international conference on Multimedia
Automated avatar creation for 3D games
Future Play '07 Proceedings of the 2007 conference on Future Play
Crafting Personalized Facial Avatars Using Editable Portrait and Photograph Example
VR '09 Proceedings of the 2009 IEEE Virtual Reality Conference
A survey on vision-based human action recognition
Image and Vision Computing
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we present an innovative framework for a 3D game character to adopt human action sequence style by learning from videos. The framework is demonstrated for kickboxing, and can be applied to other activities in which individual style includes improvisation of the sequence in which a set of basic actions are performed. A video database of a number of actors performing the basic kickboxing actions is used for feature word vocabulary creation using 3D SIFT descriptors computed for salient points on the silhouette. Next an SVM classifier is trained to recognize actions at frame level. Then an individual actor's action sequence is gathered automatically from the actor's kickboxing videos and an HMM structure is trained. The HMM, equipped with the basic repertoire of 3D actions created just once, drives the action level behavior of a 3D game character.