CCTV Based Observation for Face Masked Detector

Shraddha Taunk; Tejaswini Tikariha; Sakshi Dewangan

doi:10.59367/ijfiest.v1i1.10

Authors

Shraddha Taunk Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India
Tejaswini Tikariha Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India
Sakshi Dewangan Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India

DOI:

https://doi.org/10.59367/ijfiest.v1i1.10

Keywords:

Face detection, Viola Jones Algorithm, Feature extraction

Abstract

The utilization of CCTV observation is presently required withinside the general public and individual areas to ensure assurance against psychological oppression and burglary. Normal articulations are utilized to demonstrate a major arrangement of development credits caught in a video. Video surveillance is a famous machine wherein vital scenes aren't captured with the aid of using human intervention. The essential intention is to mechanically discover masked human beings in much less time. In this paper, the device includes 4 distinct steps: calculating the gap variety of someone from the camera, detecting eyes or eyes, and detecting components of the face consisting of the mouth and face. The overall performance of the Viola-Jones set of rules runs on loads of real-time inputs. Experimental critiques display that the Viola-Jones set of rules is advanced in phrases of time consumption. Viola-Jones algorithm is a unique approach to this problem, it creates a transparent, complex and simple way to make real-time implementations advantageous and practical. Analysis of Viola-Jones set of rules compliance at the take a look at video music offers an affordable evaluation for extra upgrades in masked face detection performance.

Author Biographies

Shraddha Taunk, Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India
Tejaswini Tikariha , Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India
Sakshi Dewangan , Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur Chhattisgarh, India

References

Scheenstra, A., Ruifrok, A. and Veltkamp, R. C.: A survey of 3D face recognition methods, Person Authentication.

Yang, G. and Huang, T. S.: Human face detection background, Pattern Recognition, 1994

Sirohey, S.A. Human face segmentation and identification, Technical report CSTR3176.

Jin, Z., Lou, Z., Yang, J. and Sun, Q.: Face detection using template matching and skin-color information, Neurocomputing.

Augusteijn, M. F. and Skujca, T. L.: Identification ofhuman faces, Proc. of IEEE Conf. Neural Networks, pp.392-398, 1993.

Rizvi, Q. M., Agarwal, B. G. and Beg, R.: A Reviewon Face Detection. Methods, https://www.researchg ate.net/publication/257338580_A_Review_on_Face_Dete ction_Methods, Qassim University, 2011.

Ping, S. T. Y., Weng, C. H. and Lau, B.: Face detection through template matching and color segmentation.

Anand, C. and Lawrance, R.: Algorithm for face recognition using HMM and SVD coefficients, Artificial Intelligent Systems and Machine Learning.

Mutelo, R. M., Khor, L. C., Woo, W. L. and Dlay, S.S.: Two-dimensional reduction PCA: A novel approach for feature extraction, representation, and recognition, Proc. of SPIE, Vol.6060, 2006.

Ahad, M. A. R.: Computer Vision and Action Recognition: A Guide for Image Processing Under- standing, Springer, 2011.

Nishina, Y., Ahad, M. A. R., Tan, J. K., Kim, H. and Ishikawa, S.: A robust face tracking method employing color-based particle filter, Int.J. of Bio-medical Soft Computing and Human Sciences.

D. P. A. A. Mr. Suman Kumar Swarnkar, ‘Improved Convolutional Neural Network based Sign Language Recognition’, International Journal of Advanced Science and Technology, vol. 27, no. 1, pp. 302–317, 2019.

V. Verma, Suman Kumar Swarnkar, and V. Swarnkar, ‘Iris Recognition System Using Adaptive Neuro Fuzzy Inference System Classifier’, 2017.

B. Chandel and Suman Kumar Swarnkar, ‘STOCK PREDICTION USING FINANCIAL DATA AND NEWS SENTIMENTAL ANALYSIS’, 2021.

Suman Kumar Swarnkar, A. Ambhaikar, V. K. Swarnkar, and U. Sinha, ‘Optimized Convolution Neural Network (OCNN) for Voice-Based Sign Language Recognition: Optimization and Regularization’, in Information and Communication Technology for Competitive Strategies (ICTCS 2020), 2020, p. 633.

S. Agarwal, J. P. Patra, and Dr Suman Kumar Swarnkar, ‘Convolutional Neural Network Architecture Based Automatic Face Mask Detection’, International Journal of Health Sciences, no. SPECIAL ISSUE III, p. 623-629, 2022.

V. S. Vivek Chandrakar and Suman Kumar Swarnkar, ‘A Naive Bayes Approach for Word Prediction using NLP’, International Journal for Scientific Research and Development, vol. 6, no. 7, pp. 401–407, 2018.

Suman Kumar Swarnkar, Ruby Chandrakar, ‘Telemedicine Cryptography using DNA Sequence’, International Journal for Research in Applied Science and Engineering Technology, vol. 5, no. 12, pp. 2122–2129, 2017.

Suman Kumar Swarnkar, Bindeshwari Chandel, ‘STOCK PREDICTION USING FINANCIAL DATA AND NEWS SENTIMENTAL ANALYSIS’, Journal of Xi’ an Shiyou University, Natural Science Edition, vol. 16, no. 9, pp. 279–285, 2020.

Suman Kumar Swarnkar, Gurpreet Singh Chhabra, Abhishek Guru, Bhawna Janghel, Prashant Kumar Tamrakar, Upasana Sinha, 'Underwater Image Enhancement Using D-Cnn', NeuroQuantology, vol. 20, no. 11, pp. 2157–2163, 2022.

Suman Kumar Swarnkar, Abhishek Guru, Gurpreet Singh Chhabra, Prashant Kumar Tamrakar, Bhawna Janghel, Upasana Sinha, 'Deep learning techniques for medical image segmentation & classification', International Journal of Health Sciences, vol. 6, no. S10, pp. 408–421, 2022.

Suman Kumar Swarnkar, Bhumika Chandrakar, ‘A Novel Appraoch for Brain Tumor Detection using SOM and Fuzzy Classifier’, International Journal of Emerging Technologies and Innovative Research, vol. 5, no. 6, pp. 413–420, 2018.

Suman Kumar Swarnkar, Ms. Preeti Bhole Mr. Suman Kumar Swarnkar, ‘HYBRID BASED RECOMMENDATION SYSTEM USING SWITCHING TECHNIQUE’, International Journal for Science and Advance Research In Technology, vol. 3, no. 11, pp. 103–109, 2017.