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SIAM Journal on Numerical Analysis
Translation-invariant mixture models for curve clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Apprenticeship learning via inverse reinforcement learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
2006 Special issue: A probabilistic model of gaze imitation and shared attention
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
IMITATION LEARNING AND ANCHORING THROUGH CONCEPTUAL SPACES
Applied Artificial Intelligence
Gestures are strings: efficient online gesture spotting and classification using string matching
Proceedings of the ICST 2nd international conference on Body area networks
Easy humanoid motion generation from user demonstration using wearable interface
ACE '08 Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology
Fusion of 2d and 3d sensor data for articulated body tracking
Robotics and Autonomous Systems
Trajectory prediction: learning to map situations to robot trajectories
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Feature representations for the recognition of 3D emblematic gestures
HBU'10 Proceedings of the First international conference on Human behavior understanding
Learning the semantics of object-action relations by observation
International Journal of Robotics Research
Mining the independent source of ERP components with ICA decomposition
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
PCA & HMM based arm gesture recognition using inertial measurement unit
BodyNets '13 Proceedings of the 8th International Conference on Body Area Networks
Comparative evaluation of performance measures for human driving skills
Intelligent Service Robotics
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This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the gesture and discards the variability intrinsic to each person's motion. We compare a decomposition into principal components (PCA) and independent components (ICA) as a first step of preprocessing in order to decorrelate and denoise the data, as well as to reduce the dimensionality of the dataset to make this one tractable. In a second stage of processing, we explore the use of a probabilistic encoding through continuous Hidden Markov Models (HMMs), as a way to encapsulate the sequential nature and intrinsic variability of the motions in stochastic finite state automata. Finally, the method is validated in a humanoid robot to reproduce a variety of gestures performed by a human demonstrator.