A Simple Yet Reliable Facial Emotion Detection for Campus Environment
Amar Lokman1, Wan Zakiah Wan Ismail2, Mus’ab Sahrim3, Sharma Rao Balakrishnan4 and Juliza Jamaludin5
1Amar Lokman Faculty of Engineering and Built Environment, USIM, Nilai, Malaysia.
2Wan Zakiah Wan Ismail*, Faculty of Engineering and Built Environment, USIM, Nilai, Malaysia.
3Mus’ab Sahrim, Faculty of Engineering and Built Environment, USIM, Nilai, Malaysia.
4Sharma Rao Balakrishnan, Faculty of Engineering and Built Environment, USIM, Nilai, Malaysia.
5Juliza Jamaludin, Faculty of Engineering and Built Environment, USIM, Nilai, Malaysia.
Manuscript received on 1 August 2019. | Revised Manuscript received on 8 August 2019. | Manuscript published on 30 September 2019. | PP: 2477-2481 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4701098319/2019©BEIESP | DOI: 10.35940/ijrte.C4701.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays, crime incidents like stealing, fighting and harassment often occur in campus leading to serious consequences. Students do not feel secure to study in campus anymore. Thus, a simple facial emotion detection system using a Raspberry Pi is introduced to help mitigating the issue before getting worse in campus. Two algorithms are used for this project including Haar Cascade and Local Binary Pattern (LBP) algorithms. OpenCV is a library that can be used for image processing. LBP algorithm is used for face detection in OpenCV. When a person enters the specified area, the camera will capture the image and detect the image of the person. Then, a rectangular box appears on the face image of the person. The image is automatically sent to the email. The face detection is enhanced by adding a face alignment. The face alignment is used to detect the location of many points on the face. It recognizes the emotions for each face and gives the confidence score. The value 0 of confidence score is the perfect face recognition. Although the system is simple, it is still reliable to be used in a campus environment.
Keywords: Face alignment, Face detection, Raspberry pi.
Scope of the Article: Smart Learning Methods and Environments