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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics

Adnan Rachmat Anom Besari

Politeknik Elektronika Negeri Surabaya (PENS) & Electronic Engineering Polytechnic Institute of Surabaya (EEPIS)

Author-ID : 3173666

Computer Science & IT Electrical & Electronics Engineering

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Face RGB-D Data Acquisition System Architecture for 3D Face Identification Technology Aldi Bayu Kreshnanda Ismail; Ihsan Fikri Abdurahman Muharram; Dadet Pramadihanto; Adnan Rachmat Anom Besari
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

The three-dimensional approach in face identification technology had gained prominent significance as the state-of-the-art breakthrough due to its ability to address the currently developing issues of identification technology (illumination, deformation and pose variance). Consequently, this trend is also followed by rapid development of the three-dimensional face identification architectures in which some of them, namely Microsoft Kinect and Intel RealSense, have become somewhat today's standard because of its popularity. However, these architectures may not be the most accessible to all due to its limited customisation nature being a commercial product. This research aims to propose an architecture as an alternative to the pre-existing ones which allows user to fully customise the RGB-D data by involving open source components, and serving as a less power demanding architecture. The architecture integrates Microsoft LifeCam and Structure Sensor as the input components and other open source libraries which are OpenCV and Point Cloud Library (PCL). The result shows that the proposed architecture can successfully perform the intended tasks such as extracting face RGB-D data and selecting out region of interest in the face area.

Automatic User-Video Metrics Creations From Emotion Detection Darari Nur Amali; Adnan Rachmat Anom Besari; Ali Ridho Barakbah; Dias Agata
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

In this digital era, digital content especially video, is increasing in number from time to time. Typically, a video service provider like Youtube will perform video analysis based on the video content such as colours, textures, shapes, and other features that exist in video content. The result of this analysis was used to understand user preference and to personalize video for each user. With technological developments, especially in Machine Learning and Computer Vision technology, video analysis can be based on other things beyond the video. In this context, it is the audience's impression. Thus, with the analysis of audience impressions in real-time, it is expected that the video can be analysed using the emotion parameters of the audience while the video is playing, and this can be done automatically and real-time. This system generates impression statistic for each video which concluded from every user who has watched the video and save those data in the database. Method used to analyse the result is by recruiting respondent and give some questionnaires. Respondents were asked to watch some videos and were asked to compare the impression metric which created by the system with user's real impression. The result shos that the automatic video-metric creation from emotion detection has been able to measure user's impression of the video with more than 80% accuracy stated by 75% of 20 respondents of the survey.

Co-Authors Aldi Bayu Kreshnanda Ismail Ali Ridho Barakbah Dadet Pramadihanto Darari Nur Amali Dias Agata Ihsan Fikri Abdurahman Muharram

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