Abstract
The research aimed to the study the development of CCTV face detection criminals and tracking system using data analysis algorithm. The proposed algorithm reduce the time spent searching for criminals and finding suspicious persons or criminals in society and precision with technology applied. It can recognize many faces. This research utilized the CCTV images to be analyzed by face detection technique. By sending a notification via text message and email. Results from Single Face Detection and group face detection were obtained as comparison. The accuracy of program was 91%. The system can recognize many faces and can be used to secure the place.
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Manlises, O., Jesus, M., Jackson, L., Czarleine, K.: Real-time integrated CCTV using face and pedestrian detection image processing algorithm for automatic traffic light transitions. In: IEEE, pp. 44–77 (2015)
Ahmed, E., Jones, M., Marks, T.K.: An improved deep learning architecture for person re-identification. In: IEEE, pp. 3908–3916 (2015)
Akshay, A., Marks, T.K., Jones, M.J., Tieu, K.H., Rohith, M.V.: Fully automatic pose-invariant face recognition via 3D pose normalization. In: IEEE International Conference on Computer Vision, pp. 937–944 (2011)
Kshirsagar, V.P., Baviskar, M.R., Gaikwad, M.E.: Face recognition using eigenfaces. In: IEEE (2011)
Xu, Y., Li, Z., Zhang, D.: A survey of dictionary learning algorithms for face recognition. In: IEEE Translation and Content Mining are Permitted for Academic Research only, pp. 1–12 (2016)
Patiyuth, P.: The study analysis knee angle of color set detection using image processing technique. In: International Conference on Signal-Image Technology & Internet Based System, pp. 657–660. IEEE (2016)
Jing, K., Wu, F., Zhu, X., Dong, X., Ma, F., Li, Z.: Multi-spectral low-rank structured dictionary learning for face recognition. Pattern Recognit. 59, 14–25 (2016)
Songyan, M., Bai, L.: A face detection algorithm based on Adaboost and new HaarLike feature. In: IEEE, pp. 651–654 (2016)
Ting, S., Shaokang, C., Conrad, S., Brian, C.: Towards robust face recognition for intelligent-CCTV based surveillance using one gallery image. In: IEEE, pp. 470–475 (2007)
Acknowledgments
This research has been financially granted by the National Research Council of Thailand and Department of Media Technology at King Mongkut’s University of Technology Thonburi. This paper presented the result of research study corresponding to the research project id number: 347920 approved by National Research Council of Thailand.
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Pramkeaw, P., Ngamrungsiri, P., Ketcham, M. (2019). CCTV Face Detection Criminals and Tracking System Using Data Analysis Algorithm. In: Theeramunkong, T., et al. Advances in Intelligent Informatics, Smart Technology and Natural Language Processing. iSAI-NLP 2017. Advances in Intelligent Systems and Computing, vol 807. Springer, Cham. https://doi.org/10.1007/978-3-319-94703-7_10
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DOI: https://doi.org/10.1007/978-3-319-94703-7_10
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