The nature of statistical learning theory
The nature of statistical learning theory
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Movement Phase in Signs and Co-Speech Gestures, and Their Transcriptions by Human Coders
Proceedings of the International Gesture Workshop on Gesture and Sign Language in Human-Computer Interaction
Recovering the Temporal Structure of Natural Gesture
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Automatic splicing for hand and body animations
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Real-time prosody-driven synthesis of body language
ACM SIGGRAPH Asia 2009 papers
Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study
Artificial Intelligence in Medicine
Recurrent kernel machines: Computing with infinite echo state networks
Neural Computation
Support Vector Echo-State Machine for Chaotic Time-Series Prediction
IEEE Transactions on Neural Networks
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Gesture analysis has been widely used for developing new methods of human-computer interaction. The advancement reached in the gesture analysis area is also motivating its application to automate tasks related to discourse analysis, such as the gesture phases segmentation task. In this paper, we present an initiative that aims at segmenting gestures, especially considering the "units" -- the larger grain involved in gesture phases segmentation. Thereunto, we have captured the gestures using a Xbox Kinect™ device, modeled the problem as a classification task, and applied Support Vector Machines. Moreover, aiming at taking advantage from the temporal aspects involved in the problem, we have used several types of data pre-processing in order to consider time domain and frequency domain features.