CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Intruder Detection System using Posture Recognition and Machine Learning

by Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 19
Year of Publication: 2021
Authors: Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain
10.5120/ijca2021921533

Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain . Intruder Detection System using Posture Recognition and Machine Learning. International Journal of Computer Applications. 183, 19 ( Aug 2021), 17-23. DOI=10.5120/ijca2021921533

@article{ 10.5120/ijca2021921533,
author = { Mainak Bhattacharya, Shiladitya Pujari, Ankit Anand, Niranjan Kumar, Sumit Kumar Jha, Aryan Raj, Sk Masum Hossain },
title = { Intruder Detection System using Posture Recognition and Machine Learning },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2021 },
volume = { 183 },
number = { 19 },
month = { Aug },
year = { 2021 },
issn = { 0975-8887 },
pages = { 17-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number19/32032-2021921533/ },
doi = { 10.5120/ijca2021921533 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:17:14.506158+05:30
%A Mainak Bhattacharya
%A Shiladitya Pujari
%A Ankit Anand
%A Niranjan Kumar
%A Sumit Kumar Jha
%A Aryan Raj
%A Sk Masum Hossain
%T Intruder Detection System using Posture Recognition and Machine Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 19
%P 17-23
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Generally, Science and technology always being persuaded when there is a need. Being secured is the utmost desire of every creatures in this world of insecurity. It is very much tough to have human security systems everywhere all the time. So in that case a system capable of atleast detection and warning of possible threats or dangers can be welcomed. In this context , one of the best way to achieve this goal is to build an intruder detection system . Intruders may be physical in nature or in case of computer networks there are network intruders also. But here in this paper it has been tried to present a comprehensive study about physical intruder detection system. In this attempt it has been presented a detailed hypothesis about intruder detection system in the light of gait recognition. It is also put in front of how research works had been done in earlier days and also used some machine learning algorithms on some human gait datasets to obtain results which is thought to give a brief idea in this domain.

References
  1. Ramanan D, Sminchisescu C (2006) Training deformable models for localization. In: IEEE computer society conference on computer vision and pattern recognition, pp 206–21.
  2. Souto H, Musse SR (2011) Automatic detection of 2D human postures based on single images. In: Sibgrapi conference on graphics,patterns and images, pp 48–55.
  3. Babu A, Dube K, Mukhopadhyay S, Ghayvat H, Jithin KMV (2016) Accelerometer based human activities and posture recognition. In: International conference on data mining and advanced computing, pp367–373
  4. Miranda L, Vieira T, Martínez D, Lewiner T, Vieira AW, Campos MFM (2014) Online gesture recognition from pose kernel learning and decision forests. Pattern Recognit Lett 39(1):65–73.
  5. Agarwal A, Triggs B (2004) 3D human pose from silhouettes by relevance vector regression. In: Proc CVPR, vol 2, ppII–882–II–888.
  6. Zainordin FD, Lee HY, Sani NA, Yong MW, Chan CS (2012) Human pose recognition using kinect and rule-based system. In:World automation congress, pp 1–6
  7. MatthewA. Turk and Alex P. Pentland. 1991. Face recognition using eigenfaces. In Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’91). IEEE, 586–591.
  8. John G. Daugman. 1993. High confidence visual recognition of persons by a test of statistical independence. IEEETransactions on Pattern Analysis and Machine Intelligence 15, 11, 1148–1161.
  9. Anil K. Jain, LinHong, Sharath Pankanti, and Ruud Bolle. 1997. An identity-authentication system using fingerprints.Proceedings of the IEEE 85, 9, 1365–1388.
  10. A. K. Jain and N. Duta. 1999. Deformable matching of hand shapes for verification. In Proceedings of International Conference on Image Processing. 857–861.
  11. Lily Lee and W. Eric L. Grimson. 2002. Gait analysis for recognition and classification. In Proceedings 5th IEEE International Conference on Automatic Face and Gesture Recognition, 2002. IEEE, 155–162.
  12. Jang Hee Yoo, Doosung Hwang, Ki Young Moon, and Mark S. Nixon. 2008. Automated human recognition by gait using neural network. In 1st Workshops on Image Processing Theory, Tools and Applications, IPTA 2008. 1–6.
  13. Peter N. Belhumeur, Joao P. Hespanha, and David J. Kriegman. 1997. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 7, 711–720.
  14. Weili Ding , Bo Hu , Han Liu, Xinming Wang , Xiangsheng Huang3 . Human posture recognition based on multiple features and rule . Learning Received: 17 June 2019 / Accepted: 2 May 2020 / Published online: 2 June 2020 . International Journal of Machine Learning and Cybernetics (2020) 11:2529–2540
  15. Aravind Sundaresan, Amit RoyChowdhury, and Rama Chellappa. 2003. A hidden Markov model based framework for recognition of humans from gait sequences. In Proceedings 2003 International Conference on Image Processing, ICIP, Vol. 2. IEEE, II–93.
  16. Nikolaos V. Boulgouris and Zhiwei X. Chi. 2007. Human gait recognition based on matching of body components. Pattern Recognition 40, 6, 1763–1770.
  17. N. V. Boulgouris and Z. X. Chi. 2007. Gait recognition using radon transform and linear discriminant analysis. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society 16, 3, 731–740.
  18. Han Su and Fenggang Huang. 2006. Gait recognition using principal curves and neural networks. In International Symposium on Neural Networks. 238–243.
  19. Springer Shmuel and Yogev Seligmann Galit. 2016. Validity of the kinect for gait assessment: A focused review.Sensors 16, 2, 194.
  20. Nikolaos V. Boulgouris and Zhiwei X. Chi. 2007. Human gait recognition based on matching of body components. Pattern Recognition 40, 6, 1763–1770.
  21. Qiong Cheng, Bo Fu, and Hui Chen. 2009. Gait recognition based on PCA and LDA. In International Symposium on Computer Science and Computational Technology (ISCSCI’09). Academy Publisher, 124–127.
  22. Xuelong Li, Stephen J. Maybank, Shuicheng Yan, Dacheng Tao, and Dong Xu. 2008. Gait components and their application to gender recognition. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 38, 2, 145–155.
  23. Jiwen Lu and Erhu Zhang. 2007. Gait recognition for human identification based on ICA and fuzzy SVM through multiple views fusion. Pattern Recognition Letters 28, 16, 2401–2411.
  24. Claudia Nickel, Tobias Wirtl, and Christoph Busch. 2012. Authentication of smartphone users based on the way they walk using k-NN algorithm. In 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing. 16–20.
  25. Chiraz BenAbdelkader, Ross Cutler, Harsh Nanda, and Larry Davis. 2001. Eigengait: Motion-based recognition of people using image self-similarity. In Audio-and Video-Based Biometric Person Authentication. Springer, 284–294.
  26. Marcin Derlatka and Mikhail Ihnatouski. 2010. Decision tree approach to rules extraction for human gait analysis. In International Conference on Artificial Intelligence and Soft Computing. 597–604.
  27. Hoppe T, Kiltz S, Dittmann J. Security Threats to Automotive CAN Networks—Practical Examples and Selected Short-Term Countermeasures. Proceedings of the 27th International Conference SAFECOMP 2008.
  28. Amit Kale, Aravind Sundaresan, A. N. Rajagopalan, Naresh P. Cuntoor, Amit K. Roy-Chowdhury, Volker Kruger, and Rama Chellappa. 2004. Identification of humans using gait. IEEE Transactions on Image Processing 13, 9, 1163–1173.
  29. Anil K. Jain, Arun Ross, and Sharath Pankanti. 2006. Biometrics: a tool for information security. IEEE Transactions on Information Forensics and Security 1, 2, 125–143.
  30. Anil Jain, Ruud Bolle, and Sharath Pankanti. 2006. Biometrics: Personal Identification in Networked Society, Volume 479. Springer Science & Business Media.
  31. Ruud M. Bolle, Jonathan Connell, Sharath Pankanti, Nalini K. Ratha, andAndrewW. Senior. 2013. Guide to Biometrics. Springer Science & Business Media.
  32. M. P. Murray. 1967. Gait as a total pattern of movement: Including a bibliography on gait. American Journal of Physical Medicine & Rehabilitation 46, 1, 290–333.
  33. Ho TK (1995) Random decision forests. In: Proceedings of the 3rd international conference on document analysis and recognition. Montreal, QC, pp 278–282
  34. Wang J, Huang Z, Zhang W, Patil A, Patil K, Zhu T, Shiroma EJ, Schepps MA, Harris TB (2017) Wearable sensor based human posture recognition. In: IEEE international conference on big data, pp 3432–3438.
  35. Lily Lee and W. Eric L. Grimson. 2002. Gait analysis for recognition and classification. In Proceedings 5th IEEE International Conference on Automatic Face and Gesture Recognition, 2002. IEEE, 155–162.
  36. Larson E, Nilsson, Dennis K, Jonsson E. An approach to specification-based attack detection for in-vehicle networks. IEEE Intelligent Vehicles Symposium 2008.
  37. Aravind Sundaresan, Amit RoyChowdhury, and Rama Chellappa. 2003. A hidden Markov model based framework for recognition of humans from gait sequences. In Proceedings 2003 International Conference on Image Processing, ICIP, Vol. 2. IEEE, II–93.
  38. Mark S. Nixon and John N. Carter. 2004. Advances in automatic gait recognition. In Proceedings 6th IEEE International Conference on Automatic Face and Gesture Recognition, 2004. IEEE, 139–144.
  39. Anil K. Jain, Arun Ross, and Salil Prabhakar. 2004. An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology 14, 1, 4–20.
  40. Gunnar Johansson. 1973. Visual perception of biological motion and a model for its analysis. Perception & Psychophysics 14, 2, 201–211.
  41. Chen K, Wang Q (2016) Human posture recognition based on skeleton data. In: IEEE international conference on progress in informatics and computing, pp 618–622
  42. M. P. Murray, A. B. Drought, and R. C. Kory. 1964.Walking patterns of normal men. Journal of Bone & Joint Surgery American Volume 46, 2, 335.
  43. Davrondzhon Gafurov. 2007. A survey of biometric gait recognition: Approaches, security and challenges. In Annual Norwegian Computer Science Conference, 19–21
  44. Peter N. Belhumeur, Joao P. Hespanha, and David J. Kriegman. 1997. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 7, 711–720.
  45. I. Haritaoglu, D. Harwood and L. S. Davis, “Ghost : A Human Body Part Labeling System Using Silhouettes,” 14th International Conference on Pattern Recognition, 1998, Brisbane, Australia.
Index Terms

Computer Science
Information Sciences

Keywords

Posture Recognition Intruder Gait recognition

Powered by PhDFocusTM