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E-raamat: Computational Intelligence for Human Action Recognition [Taylor & Francis e-raamat]

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Computational Intelligence for Human Action RecognitionSuurem pilt
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Human Action Recognition is a challenging area presently. The vigor of research effort directed towards this domain is self indicative of this. With the ever-increasing involvement of Computational Intelligence in our day to day applications, the necessity of human activity recognition has been able to make its presence felt to the concerned research community. The primary drive of such an effort is to equip the computing system capable of recognizing and interpreting human activities from posture, pose, gesture, facial expression etc. The intent of human activity recognition is a formidable component of cognitive science in which researchers are actively engaged of late.

Features:











A systematic overview of the state-of-the-art in computational intelligence techniques for human action recognition.





Emphasized on different intelligent techniques to recognize different human actions.





Discussed about the automation techniques to handle human action recognition.





Recent research results and some pointers to future advancements in this arena.

In the present endeavour the editors intend to come out with a compilation that reflects the concerns of relevant research community. The readers would be able to come across some of the latest findings of active researchers of the concerned field.

It is anticipated that this treatise shall be useful to the readership encompassing students at undergraduate and postgraduate level, researchers active as well as aspiring, not to speak of the senior researchers.
Preface xi
Editors xv
Contributors xix
Chapter 1 Recent Advancements in Automatic Sign Language Recognition (SLR)
1(24)
Varshini Prakash
B.K. Tripathy
1.1 Introduction
2(2)
1.1.1 Common Challenges Faced in SLR
2(1)
1.1.2 Approach
3(1)
1.2 Models Used For Slr
4(13)
1.2.1 Hidden Markov Model
4(3)
1.2.2 Gaussian Mixture Model
7(2)
1.2.3 Neural Networks
9(1)
1.2.4 Convolutional Neural Network: Hidden Markov Model
10(2)
1.2.5 3D Convolutional Neural Network
12(2)
1.2.6 Restricted Boltzmann Machine
14(2)
1.2.7 Adaptive Pooling and Capsule Network
16(1)
1.3 Current Applications
17(1)
1.3.1 Hand Gesture Recognition System
17(1)
1.3.2 Sensory Gloves
18(1)
1.4 Conclusion And Future Scope
18(2)
Glossary
20(1)
Further Reading
20(1)
Bibliography
20(5)
Chapter 2 Distance-Shape-Texture Signature Trio for Facial Expression Recognition
25(28)
Asit Barman
Sankhayan Chodhury
Paramartha Dutta
2.1 Introduction
26(1)
2.2 Overview Of The Proposed System
27(1)
2.3 Facial Landmark Detection
28(6)
2.3.1 Grid Formation
30(1)
2.3.1.1 Distance Signature
30(1)
2.3.2 Triangle Formation
31(1)
2.3.2.1 Shape Signature
31(1)
2.3.3 Texture Region
32(1)
2.3.4 Local Binary Pattern
32(1)
2.3.4.1 Texture Signature
33(1)
2.4 Formation Of Distance-Shape-Texture Signature Trio For Feature Extraction
34(1)
2.4.1 Stability Index of Distance-Shape-Texture signature trio
34(1)
2.4.2 Statistical measures from Distance-Shape-Texture signature trio
35(1)
2.5 Feature Selection Of Distance-Shape-Texture Signature Trio
35(1)
2.6 Classification Of Distance-Shape-Texture Signature Trio Features
36(2)
2.6.1 Multilayer Perceptron
36(1)
2.6.2 Training using Nonlinear Auto Regressive with exogenous input
37(1)
2.6.3 Radial Basis Network
37(1)
2.7 Experiment And Result
38(9)
2.7.1 Experiment on CK+ Database
38(2)
2.7.2 Experiment on JAFFE Dataset
40(1)
2.7.3 Experiment on MMI Database
41(2)
2.7.4 Experiment on MUG Database
43(3)
2.7.5 Comparison Analysis with Three Artificial Networks and State-of-the-Arts
46(1)
2.8 Conclusion
47(1)
Bibliography
47(6)
Chapter 3 Face Expression Recognition using Side Length Features Induced by Landmark Triangulation
53(20)
Avishek Nandi
Paramahtha Dutta
Md Nasir
3.1 Introduction
54(1)
3.2 Related Works
55(1)
3.3 Gap Analysis
56(1)
3.4 Motivation
56(1)
3.5 Proposed Methodology
57(6)
3.5.1 Facial Component Detection
57(1)
3.5.2 Formation of Triangles
58(1)
3.5.3 Feature Extraction
59(3)
3.5.4 Classification Learning
62(1)
3.6 Discussions And Performance Comparisons
63(6)
3.6.1 Results on CK+ Database
63(1)
3.6.2 Results on JAFFE database
64(2)
3.6.3 Results on MMI database
66(1)
3.6.4 Results on MUG database
67(2)
3.7 Conclusions
69(1)
3.8 Acknowledgments
69(1)
Bibliography
70(3)
Chapter 4 A Study on the Influence of Angular Signature of Landmark Induced Triangulation in Recognizing Changes in Human Emotion
73(30)
Md Nasir
Paramartha Dutta
Avishek Nandi
4.1 Introduction
74(1)
4.2 Proposed Method
75(9)
4.2.1 Landmark Identification
76(3)
4.2.2 Geometric Feature Extraction
79(2)
4.2.2.1 Formation of Angular Signature Matrix (ASM) by Triangulation mechanism
81(3)
4.2.3 Emotion Classification
84(1)
4.3 Results And Discussion
84(9)
4.3.1 Experiment on CK+ Database
85(1)
4.3.2 Experiment on MUG Database
86(3)
4.3.3 Experiment on MMI Database
89(4)
4.4 Comparison With Other Work
93(2)
4.5 Conclusion
95(3)
4.6 Acknowledgment
98(1)
Bibliography
99(4)
Chapter 5 A Behavioural Model for Persons with Autism Based on Relevant Case Study
103(22)
Rudranath Banerjee
Sourav De
Shouvik Dey
5.1 Introduction
104(3)
5.2 Review Of Related Works
107(2)
5.3 Methodology Of The Case Study
109(4)
5.3.1 Study Design
109(1)
5.3.2 Participants
110(1)
5.3.3 Study Assessment Scale
111(1)
5.3.4 Technical Modules
112(1)
5.3.5 Clinical Modules
112(1)
5.4 Results And Discussion
113(5)
5.5 Conclusion
118(1)
Acknowledgment
118(1)
Further Reading
118(7)
Index 125
Dr Sourav De has been as an Associate Professor in the Department of Computer Science and Engineering in Cooch Behar Government Engineering College, Cooch Behar since April 2016. His areas of interests are Soft Computing, Image Processing, Data Mining, Evolutionary Computation etc. Dr Sourav De has been as an Associate Professor in the Department of Computer Science and Engineering in Cooch Behar Government Engineering College, Cooch Behar since April 2016. His areas of interests are Soft Computing, Image Processing, Data Mining, Evolutionary Computation etc.

Dr Paramartha Dutta is a Professor in Department of Computer & System Sciences in Visva-Bharati in West Bengal. His areas of interests are Soft Computing, Image Processing, Data Mining, Evolutionary Computation etc. He has coauthored eight books and has also eleven edited books with leading publishing houses such as Springer, Elsevier, John Wiley, Taylor and Francis, IGI Global etc. to his credit. He has published more than two hundred papers in various journals and conference proceedings, both international and national as well as several book chapters in edited volumes of reputed International publishing houses like Elsevier, Springer-Verlag, CRC Press, John Wiley, IGI Global to name a few. Dr. Dutta has guided seven scholars who already had been awarded their Ph. D. In addition, three of his scholars have submitted their Ph. D theses. Presently, he is supervising six scholars registered for their Ph. D program. Dr. Dutta is the coinventor of six published Indian Patents and one published International Patent.
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