Abedante, John Paul G., author. <br/><br/>
Facial Recognition System for Car Ignition using OpenCV, DLIB Framework and Raspberry Pi 3 Model B / 
John Paul G. Abedante. 
 - Rosario, Cavite :  Cavite State University-CCAT Campus,  2018 
 - xiii, 58 leaves :  illustrations ;  28 cm 
<br/><br/> Design Project (BSCpE)--Cavite State University-CCAT Campus, 2018. 
<br/><br/>Includes bibliographical references and appendices. 
<br/><br/> 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: Mrs. Diane P. Arayata. Technical adviser: Fernando M. Cielo.<br/><br/>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. <br/><br/>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. <br/><br/>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. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Human face recognition.<br/>Facial recognition.<br/>Amperage draw.<br/>Face recognition algorithm.<br/>DLIB framework.<br/>Raspberry Pi.<br/>Face detection.<br/>Car ignition.
<br/><br/><label>LC Class. No.: </label>UM TK 7870  / E88 2017