Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B /
Abendante, John Paul G., author.
Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B / John Paul G. Abendante - Rosario, Cavite : Cavite State University-CCAT Campus, 2018 - xiii, 58 leaves : illustrations ; 28 cm
Design Project (BSCpE)--Cavite State University-CCAT Campus, 2018.
Includes bibliographical references and appendices.
ABENDANTE, JOHN PAUL G. Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B. Design Project. Department of Engineering. Cavite State University-Cavite College of Arts and Trades Campus, Rosario, Cavite. June 2018. Adviser: Diane P. Arayata. Technical critic: Fernando M. Cielo.
The study was conducted from May 2017 to March 2018 to create a system to ignite a car engine using facial recognition. Specifically, the study aimed to: 1) develop a device that will manage the car’s ignition without the use of a key; 2) evaluate the speed of the system’s initialization; 3) conduct an accuracy test for the face recognition system; 4) test the device for its durability ; and 5) measure the amperage draw of the device.
The device was tested by involving 6 participants that were divided into 2 categories the registered and the unregistered individuals. Each subject has undergone 3 consecutive trials.
The results of the evaluation revealed that the system’s face recognition algorithm used was reliable, but was considered inefficient due to the high initialization time which is about 1 minute. The accuracy is affected by different poses and illumination.
Human face recognition.
Facial recognition.
Amperage draw.
Face recognition algorithm.
DLIB Framework.
Raspberry Pi
Face detection.
Ca ignition.
UM TA 1637 / A24 2018
Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B / John Paul G. Abendante - Rosario, Cavite : Cavite State University-CCAT Campus, 2018 - xiii, 58 leaves : illustrations ; 28 cm
Design Project (BSCpE)--Cavite State University-CCAT Campus, 2018.
Includes bibliographical references and appendices.
ABENDANTE, JOHN PAUL G. Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B. Design Project. Department of Engineering. Cavite State University-Cavite College of Arts and Trades Campus, Rosario, Cavite. June 2018. Adviser: Diane P. Arayata. Technical critic: Fernando M. Cielo.
The study was conducted from May 2017 to March 2018 to create a system to ignite a car engine using facial recognition. Specifically, the study aimed to: 1) develop a device that will manage the car’s ignition without the use of a key; 2) evaluate the speed of the system’s initialization; 3) conduct an accuracy test for the face recognition system; 4) test the device for its durability ; and 5) measure the amperage draw of the device.
The device was tested by involving 6 participants that were divided into 2 categories the registered and the unregistered individuals. Each subject has undergone 3 consecutive trials.
The results of the evaluation revealed that the system’s face recognition algorithm used was reliable, but was considered inefficient due to the high initialization time which is about 1 minute. The accuracy is affected by different poses and illumination.
Human face recognition.
Facial recognition.
Amperage draw.
Face recognition algorithm.
DLIB Framework.
Raspberry Pi
Face detection.
Ca ignition.
UM TA 1637 / A24 2018