Interactive Design of 3D Dynamic Gesture Based on SVM-LSTM Model

Visualhandgestureinteractionisoneofthemainwaysofhuman-computerinteraction,andprovides usersmoreinteractivedegreesoffreedomandmorerealisticinteractiveexperience.Authorspresent ahybridmodelbasedonSVM-LSTM,anddesignathree-dimensionaldynamicgestureinteraction system. The system uses Leap Motion to capture gesture information, combined with SVM powerfulstaticgestureclassificationabilityandLSTMpowerfulvariable-lengthtimeseriesgesture processingability,enablingreal-timerecognitionofusergestures.Thegestureinteractionmethod canautomaticallydefinethestartandendofgestures,recognitionaccuracyreached96.4%,greatly reducingthecostoflearning.Experimentshaveshownthatthegestureinteractionmethodproposed byauthorsiseffective.Inthesimulatedmobileenvironment, theaveragegesturepredictiononly takes0.15seconds,andordinaryuserscanquicklygraspthismethod. KeywoRDS 3D, Hand Gesture, Human-Computer Interaction, Leap Motion, LSTM, Neural Networks, Real-Time, SVM

[1]  Jake Araullo,et al.  The Leap Motion controller: a view on sign language , 2013, OZCHI.

[2]  Jianwei Liu,et al.  MCR SVM classifier with group sparsity , 2016 .

[3]  Huosheng Hu,et al.  A robot calligraphy system: From simple to complex writing by human gestures , 2017, Eng. Appl. Artif. Intell..

[4]  Jürgen Schmidhuber,et al.  Bidirectional LSTM Networks for Improved Phoneme Classification and Recognition , 2005, ICANN.

[5]  S. Abdul-Kareem,et al.  RETRACTED ARTICLE: Static hand gesture recognition using neural networks , 2014, Artificial Intelligence Review.

[6]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[7]  Heiga Zen,et al.  Fast, Compact, and High Quality LSTM-RNN Based Statistical Parametric Speech Synthesizers for Mobile Devices , 2016, INTERSPEECH.

[8]  Gallayanee Yaoyuneyong,et al.  Factors impacting the efficacy of augmented reality virtual dressing room technology as a tool for online visual merchandising , 2014 .

[9]  Jianwei Zhang,et al.  Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task , 2016, CAAI Trans. Intell. Technol..

[10]  Buket D. Barkana,et al.  Performance analysis of descriptive statistical features in retinal vessel segmentation via fuzzy logic, ANN, SVM, and classifier fusion , 2017, Knowl. Based Syst..

[11]  Jiali Zhang,et al.  Dynamic gesture recognition and human-computer interaction , 2015 .

[12]  Hsiang Yueh Lai,et al.  Real-Time Dynamic Hand Gesture Recognition , 2014, 2014 International Symposium on Computer, Consumer and Control.

[13]  X Yao,et al.  Application of two-class SVM applied in landslide susceptibility mapping , 2013 .

[14]  Bo Xiao,et al.  A real-time vision-based hand gesture interaction system for virtual EAST , 2016 .

[15]  Emil M. Petriu,et al.  Hand gesture detection and recognition using principal component analysis , 2011, 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings.

[16]  Yiding Wang,et al.  3D hand gesture recognition based on Polar Rotation Feature and Linear Discriminant Analysis , 2013, 2013 Fourth International Conference on Intelligent Control and Information Processing (ICICIP).

[17]  Hong Zhang,et al.  A novel hybrid-Garch model based on ARIMA and SVM for PM2.5 concentrations forecasting , 2017 .

[18]  Seongah Chin,et al.  Designing Canonical Form of Finger Motion Grammar in Leapmotion Contents , 2016 .

[19]  Belkacem Brahmi,et al.  A primal-dual method for SVM training , 2016, Neurocomputing.

[20]  侯建峰,et al.  基于Unity3D的体感游戏设计与实现 The Design and Implementation of Motion Sensing Game Based on Unity 3D , 2016 .

[21]  Yi Li,et al.  Hand gesture recognition using Kinect , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering.

[22]  Chuanlei Yang,et al.  Investigation of ANN and SVM based on limited samples for performance and emissions prediction of a CRDI-assisted marine diesel engine , 2017 .

[23]  Huaqing Wang,et al.  Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR , 2010, Sensors.

[24]  J. Platt Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[25]  Youping Deng,et al.  SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data , 2006, BMC Bioinformatics.

[26]  Jürgen Schmidhuber,et al.  Learning to Forget: Continual Prediction with LSTM , 2000, Neural Computation.

[27]  Yunfei Chen,et al.  Analysis of Spectrum Occupancy Using Machine Learning Algorithms , 2015, IEEE Transactions on Vehicular Technology.

[28]  B Waghmare Amit,et al.  Augmented Reality for Information Kiosk , 2014 .