Phankokkruad, Manop

Loading...
Thumbnail Image
Preferred name
Phankokkruad, Manop
Main Affiliation
Email
manop.ph@kmitl.ac.th

Settings

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    An evaluation of technical study and performance for real-time face detection using Web Real-Time Communication
    (2015-08-24)
    Phankokkruad, Manop
    ;
    Jaturawat, Phichaya
    This paper proposed the technical study of real-time face detection system and also cover a key technology. In order to find the most appropriate factors, techniques, and algorithm by evaluating the performance that included connection speed, and effectiveness of tracking and detecting a human face in various conditions. WebRTC worked perform in any condition of device and platform independence. Furthermore, WebRTC could operate securely on the HTTPS protocol. In the case of the transferring ability of images, it relied on the connection speed; that LAN and WiFi are the most prefer for this best image quality. The results shown that Haar-like feature and CLM have significantly detected the face area over the web browser in almost light conditions. However, Haar-like has the better precision when operated on the low-speed processor. The real-time face detection system could be identified the person who walked through the capture device. In addition, this proposed system could be applied to any scope of the personal identification system.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A real-time face recognition for class participation enrollment system over WebRTC
    (2016-01-01)
    Phankokkruad, Manop
    ;
    Jaturawat, Phichaya
    ;
    Pongmanawut, Pasinee
    In the classroom, students can get the most benefit for themselves when attend and participate in the classroom. Roll-call is a classical method that mostly uses for the class participation enrollment. The time that used for this method is depended on the number of students; the more number of students, the more time to spend. This work presents the method that improves the class participation enrollment process Thus, we developed the face detection and face recognition system by applying the WebRTC. Since it is a platform independent, we could capture the participant faces from anywhere without an installation. In addition, the three standard face detection and recognition algorithms were applied in two main processes properly. The result showed that system can improve the class participation enrollment accuracy to be more precise and persuaded the student to attend the class as well. Moreover, the system can install to the classroom easily because it is developed in form of the web application and needs an only web camera for the additional device.