Optimization of a HMM-based hand gesture recognition system using a hybrid cuckoo search algorithm

The authors develop an advanced hand motion recognition system for virtual reality applications using a well defined stochastic mathematical approach. Hand gesture is a natural way of interaction with a computer by interpreting the primitive characteristics of gesture movement to the system. This concerns three basic issues: (1) there is no physical contact between the user and the system, (2) the rotation of the hand gesture can be determined by the geometric features, and (3) the model parameter must be optimized to improve measurement of performance. A comparative analysis of other classification techniques used in hand gesture recognition is carried out on the proposed work hybrid with the bio-inspired metaheuristic approach, namely the cuckoo search algorithm, for reducing the complex trajectory in the hidden Markov model (HMM) model. An experimental result is as to how to validate the HMM model, based on the cost value of the optimizer, in order to improve the performance measures of the system.

[1]  Mohammed Azmi Al-Betar,et al.  β\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}-Hill climbing: an exploratory local search , 2016, Neural Computing and Applications.

[2]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[3]  Jr. G. Forney,et al.  The viterbi algorithm , 1973 .

[4]  Rong Li,et al.  Text Information Extraction Based on Genetic Algorithm and Hidden Markov Model , 2009, 2009 First International Workshop on Education Technology and Computer Science.

[5]  Weihua Sheng,et al.  Human-guided robot 3D mapping using virtual reality technology , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[6]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[7]  D. Jude Hemanth,et al.  Hand posture and gesture recognition techniques for virtual reality applications: a survey , 2016, Virtual Reality.

[8]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[9]  Ilya Pavlyukevich.  Lévy flights, non-local search and simulated annealing , 2007, J. Comput. Phys..

[10]  K. Martin Sagayam,et al.  Application of Pseudo 2-D Hidden Markov Model for Hand Gesture Recognition , 2017 .

[11]  Mohammed Azmi Al-Betar,et al.  A survey on applications and variants of the cuckoo search algorithm , 2017, Appl. Soft Comput..

[12]  Sourav Bhowmick,et al.  Hand gesture recognition of English alphabets using artificial neural network , 2015, 2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS).

[13]  Radu-Laurentiu Vieriu,et al.  Background invariant static hand gesture recognition based on Hidden Markov Models , 2013, International Symposium on Signals, Circuits and Systems ISSCS2013.

[14]  Rikard Berthilsson,et al.  Real Time Viterbi Optimization of Hidden Markov Models for Multi Target Tracking , 2007, 2007 IEEE Workshop on Motion and Video Computing (WMVC'07).

[15]  Ramin Rajabioun,et al.  Cuckoo Optimization Algorithm , 2011, Appl. Soft Comput..

[16]  Alisha Pradhan,et al.  Design of Intangible Interface for Mouseless Computer Handling using Hand Gestures , 2016 .

[17]  H. Stanley,et al.  Lévy flight random searches in biological phenomena , 2002 .

[18]  John R. Koza,et al.  Genetic programming 2 - automatic discovery of reusable programs , 1994, Complex Adaptive Systems.

[19]  Clifford T. Brown,et al.  Lévy Flights in Dobe Ju/’hoansi Foraging Patterns , 2007 .

[20]  Zhenbang Gong,et al.  Low Cost Hand Gesture Learning and Recognition System Based on Hidden Markov Model , 2009, 2009 Second International Symposium on Information Science and Engineering.

[21]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[22]  Yi Li,et al.  Dynamic hand gesture recognition using hidden Markov models , 2012, 2012 7th International Conference on Computer Science & Education (ICCSE).

[23]  Thomas Mailund,et al.  Ancestral population genomics using coalescence hidden Markov models and heuristic optimisation algorithms , 2015, Comput. Biol. Chem..

[24]  Xin-She Yang,et al.  Cuckoo search: recent advances and applications , 2013, Neural Computing and Applications.

[25]  José Barata,et al.  Hand Gesture Recognition towards Enhancing Accessibility , 2015, DSAI.

[26]  Mohammed Azmi Al-Betar,et al.  comprehensive review : Krill Herd algorithm ( KH ) and its pplications saju , 2016 .

[27]  Rainer Storn,et al.  Minimizing the real functions of the ICEC'96 contest by differential evolution , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[28]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[29]  Slawomir Koziel,et al.  Computational Optimization, Methods and Algorithms , 2016, Computational Optimization, Methods and Algorithms.

[30]  H. Stanley,et al.  Optimizing the success of random searches , 1999, Nature.

[31]  Chuanqi Li,et al.  Optimization of Hidden Markov Model by a Genetic Algorithm for Web Information Extraction , 2007 .

[32]  F. Glover.  HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[33]  N.D. Georganas,et al.  A dynamic gesture interface for virtual environments based on hidden Markov models , 2005, IEEE International Workshop on Haptic Audio Visual Environments and their Applications.

[34]  Samir Otmane,et al.  A discrete Hidden Markov models recognition module for temporal series: Application to real-time 3D hand gestures , 2012, 2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA).

[35]  Martin Buss,et al.  Handshake: Realistic Human-Robot Interaction in Haptic Enhanced Virtual Reality , 2011, PRESENCE: Teleoperators and Virtual Environments.

[36]  Toby Sharp,et al.  Real-time human pose recognition in parts from single depth images , 2011, CVPR.

[37]  S. Govindarajulu,et al.  A Comparison of SIFT, PCA-SIFT and SURF , 2012 .

[38]  Patrik Kamencay,et al.  Comparison of SIFT and SURF Methods for Use on Hand Gesture Recognition based on Depth Map , 2014 .

[39]  Iztok Fister,et al.  Cuckoo Search: A Brief Literature Review , 2014, ArXiv.

[40]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[41]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[42]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[43]  Koffka Khan,et al.  Neural-Based Cuckoo Search of Employee Health and Safety (HS) , 2013 .

[44]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[45]  Kandarpa Kumar Sarma,et al.  Stereo Vision-based Hand Gesture Recognition under 3D Environment , 2015 .

[46]  Gyanendra K. Verma,et al.  Human Computer Interaction using Hand Gesture , 2015 .

[47]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[48]  F Sachs,et al.  A direct optimization approach to hidden Markov modeling for single channel kinetics. , 2000, Biophysical journal.

[49]  K. Martin Sagayam,et al.  Comparative Analysis of 1-D HMM and 2-D HMM for Hand Motion Recognition Applications , 2018 .