UTHM Institutional Repository

Effective geometric calibration and facial feature extraction using multi sensors

Mohd, Mohd Norzali and Kashima, Masayuki and Sato, Kiminori and Watanabe, Mutsumi (2012) Effective geometric calibration and facial feature extraction using multi sensors. International Journal of Engineering Science and Innovative Technology (IJESIT), 1 (2). pp. 170-178. ISSN 2319-5967


Download (655kB)


This paper aims to present facial feature extraction by integrating 3 different sensors that might be used in the estimation of internal mental state. RGB-D camera is used at the pre and post monitoring phase while thermal infrared and visible camera is being used in the stimulus experiment. The measurement of three facial areas of sympathetic importance through purely imaging means that is periorbital, supraorbital and maxillary is done on the second stage. An Accurate and efficient thermal-infrared camera calibration is important for advancing computer vision research approach for geometrically calibrating individual and multiple cameras in both thermal and visible modalities. We also propose new printed Fever Cold Plaster (FCP) chessboard using a popular existing approach which is comparatively accurate and simple to execute. Based on the experiment conducted by comparing the degradation of image quality with the current approach, our proposed chessboard can be more clearly located than those on the applied standard chessboard by 39%.

Item Type: Article
Uncontrolled Keywords: thermal-infrared geometric camera calibration; thermal face; facial feature extraction
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 17 Dec 2014 08:16
Last Modified: 17 Dec 2014 08:16
URI: http://eprints.uthm.edu.my/id/eprint/6131
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item


Downloads per month over past year