Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera
Detection and prevention of criminal incidents using CCTV are currently increasing trend, for example, car and motorcycle parking lot. However, not continuous people monitoring and careless of events produce useless CCTV function for the prevention of criminal incidents. In this paper, face recognit...
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/30064/ http://umpir.ump.edu.my/id/eprint/30064/1/08982383.pdf http://umpir.ump.edu.my/id/eprint/30064/7/Face%20recognition%20using%20faster%20R-CNN.pdf |
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| author | Halawa, Lavin J. Wibowo, A. Ernawan, Ferda |
| author_facet | Halawa, Lavin J. Wibowo, A. Ernawan, Ferda |
| author_sort | Halawa, Lavin J. |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Detection and prevention of criminal incidents using CCTV are currently increasing trend, for example, car and motorcycle parking lot. However, not continuous people monitoring and careless of events produce useless CCTV function for the prevention of criminal incidents. In this paper, face recognition is used for the recognition of vehicle owners in parking lots that are CCTV installed. The Faster-RCNN method is used for face detection and also for face recognition. Inception V2 architecture is utilized due to has a high accuracy among Convolutional Neural Network architecture. The best learning rate and epoch parameters for the Faster R-CNN model are optimized to improve face recognition on CCTV. In this research, the dataset consists of 6 people images with 50 faces images for each people, which used as training data, testing data, and validation data. |
| first_indexed | 2025-11-15T02:56:57Z |
| format | Conference or Workshop Item |
| id | ump-30064 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T02:56:57Z |
| publishDate | 2019 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-300642023-12-15T04:10:44Z http://umpir.ump.edu.my/id/eprint/30064/ Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera Halawa, Lavin J. Wibowo, A. Ernawan, Ferda QA75 Electronic computers. Computer science Detection and prevention of criminal incidents using CCTV are currently increasing trend, for example, car and motorcycle parking lot. However, not continuous people monitoring and careless of events produce useless CCTV function for the prevention of criminal incidents. In this paper, face recognition is used for the recognition of vehicle owners in parking lots that are CCTV installed. The Faster-RCNN method is used for face detection and also for face recognition. Inception V2 architecture is utilized due to has a high accuracy among Convolutional Neural Network architecture. The best learning rate and epoch parameters for the Faster R-CNN model are optimized to improve face recognition on CCTV. In this research, the dataset consists of 6 people images with 50 faces images for each people, which used as training data, testing data, and validation data. IEEE 2019-10 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/30064/1/08982383.pdf pdf en http://umpir.ump.edu.my/id/eprint/30064/7/Face%20recognition%20using%20faster%20R-CNN.pdf Halawa, Lavin J. and Wibowo, A. and Ernawan, Ferda (2019) Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera. In: 3rd International Conference on Informatics and Computational Sciences, ICICOS 2019 , 29 - 30 October 2019 , Semarang, Indonesia. pp. 1-6. (8982383). ISBN 978-172814610-2 (Published) https://doi.org/10.1109/ICICoS48119.2019.8982383 |
| spellingShingle | QA75 Electronic computers. Computer science Halawa, Lavin J. Wibowo, A. Ernawan, Ferda Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title | Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title_full | Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title_fullStr | Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title_full_unstemmed | Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title_short | Face recognition using faster R-CNN with inception-V2 architecture for CCTV camera |
| title_sort | face recognition using faster r-cnn with inception-v2 architecture for cctv camera |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/30064/ http://umpir.ump.edu.my/id/eprint/30064/ http://umpir.ump.edu.my/id/eprint/30064/1/08982383.pdf http://umpir.ump.edu.my/id/eprint/30064/7/Face%20recognition%20using%20faster%20R-CNN.pdf |