Annoyance and frustration software using image processing for computer users / by Ezra Jeremiah P. Anglo and Menisa Bella A. Mendoza
Material type: TextLanguage: English Publication details: Indang, Cavite : Cavite State University- Main Campus, 2014.Description: xiv, 113 pages : illustrations ; 28 cmContent type:- text
- unmediated
- volume
- 006.42 An4 2014
- College of Engineering, and Information Technology (CEIT)
Item type | Current library | Collection | Call number | Materials specified | URL | Status | Notes | Date due | Barcode |
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Theses / Manuscripts | Ladislao N. Diwa Memorial Library Theses Section | Non-fiction | 006.42 An4 2014 (Browse shelf(Opens below)) | Link to resource | Room use only | T-5331 | 00008602 |
Thesis (BS Computer Science) Cavite State University
Includes bibliographical references.
College of Engineering, and Information Technology (CEIT)
NGLO, EZRA JEREMIAH P., MENDOZA, MENISA BELLA A. An Annoyance and Frustration Emotion Recognition Software Using Image Processing for Computer Users. Undergraduate Thesis. Bachelor of Science in Computer Science. Cavite State University, Indang, Cavite April 2014. Adviser: Ms. Charlotte B. Carandang .
The study was conducted at Cavite State University College of Engineering and Information Technology. The study aimed to recognize annoyance and frustration emotion of computer users using image processing. A total of twenty faculty members of the Department of Information Technology as the respondents and were potential used of the software. The study was carried out from January 2013 to March 2014.
Software Development Methodology was used in the completing the study. The methodology consist of analyze/planning, breakdown priority project, design module, code test, debug, integration of sub procedure and testing, integration of sub procedure and test and implementation phase. Statistical analysis was used.
Frustration-Annoyance Classification Software (FACS) saw the developed software. It uses web camera to capture images. The system detects face from the captures image the traces the facial feature to gather data and then compares to the pre-defined trained data to acquire results. The software displays the percentage of chances of having frustration/annoyance from the face image which is the results. The findings of the study revealed a positive perception by the respondents who were potentially users of the software.
Submitted to the University Library 8-4-2020 T-5331