DocumentCode
446024
Title
Temporal hand gesture recognition by fuzzified TSK-type recurrent fuzzy network
Author
Juang, Chia-Feng ; Ku, Ksuan-Chun ; Chen, Shin-Kuan
Author_Institution
Dept. of Electr. Eng., Nat. Chung Hsing Univ., Taichung, Taiwan
Volume
3
fYear
2005
fDate
31 July-4 Aug. 2005
Firstpage
1848
Abstract
Temporal hand gesture recognition by fuzzified Takagi-Sugeno-Kang (TSK)-type recurrent fuzzy network (FTRFN) is proposed in this paper. The temporal hand gesture is captured by CCD and represented by a two-dimensional fuzzy trajectory. To handle fuzzy trajectories, FTRFN is employed. The inputs and outputs of FTRFN are fuzzy patterns represented by Gaussian membership functions, and the recurrent property of FTRFN enables it to deal with fuzzy patterns with temporal context. In recognition scheme, the FTRFN performs trajectory recognition by prediction instead of classification. Experiments on ten categories of gestures are performed to verify the proposed approach.
Keywords
CCD image sensors; Gaussian processes; fuzzy neural nets; fuzzy set theory; gesture recognition; image representation; pattern recognition; recurrent neural nets; CCD; Gaussian membership function; fuzzified TSK-type recurrent fuzzy network; fuzzified Takagi-Sugeno-Kang network; fuzzy pattern; fuzzy trajectory; hand gesture recognition; trajectory recognition; Charge coupled devices; Fingers; Fuzzy neural networks; Fuzzy sets; Hidden Markov models; Human computer interaction; Neural networks; Speech recognition; Takagi-Sugeno-Kang model; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN
0-7803-9048-2
Type
conf
DOI
10.1109/IJCNN.2005.1556161
Filename
1556161
Link To Document