Sciweavers

Share
WIAMIS
2009
IEEE

Adaptive gesture recognition in Human Computer Interaction

9 years 10 months ago
Adaptive gesture recognition in Human Computer Interaction
An adaptive, invariant to user performance fluctuation or noisy input signal, gesture recognition scheme is presented based on Self Organizing Maps, Markov Models and Levenshtein sequence distance. Multiple modalities, all based on the hand position during gesturing, train different classifiers which are then fused in a weak classifier boosting-like setup by weight assignment to each stream. The adaptability of the proposed approach consists of the incorporation of Self Organizing Maps during training, the exploitation of neighboring relations between states of the Markov models and the modified Levenshtein distance algorithm. The main focus of current work is to tackle intra and inter user variability during gesture performance by adding flexibility to the decoding procedure and allowing the algorithm to perform an optimal trajectory search while the processing speed of both the feature extraction and the recognition process indicate that the proposed architecture is appropriate...
George Caridakis, Kostas Karpouzis, Athanasios I.
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where WIAMIS
Authors George Caridakis, Kostas Karpouzis, Athanasios I. Drosopoulos, Stefanos D. Kollias
Comments (0)
books