Development of affective state recognition model based on thermal imaging /

In social interaction, the explicit and implicit communication plays a significant role in an effective interaction. However, the typical modalities of interaction such as verbal and body language, sometimes, may be deterred causing meaningful communication could not be achieved especially when deal...

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Bibliographic Details
Main Author: Muhamad Hafiz b. Abd Latif
Format: Thesis
Language:English
Published: Gombak, Selangor : Kulliyyah of Engineering, International Islamic University Malaysia, 2016
Subjects:
Online Access:Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library.
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040 |a UIAM  |b eng 
041 |a eng 
043 |a a-my--- 
050 |a QA76.9.H85 
100 0 |a Muhamad Hafiz b. Abd Latif 
245 1 |a Development of affective state recognition model based on thermal imaging /  |c by Muhamad Hafiz b. Abd Latif 
260 |a Gombak, Selangor :  |b Kulliyyah of Engineering, International Islamic University Malaysia,  |c 2016 
300 |a xv, 116 leaves :  |b ill. ;  |c 30cm. 
500 |a Abstracts in English and Arabic. 
500 |a "A thesis submitted in fulfilment of the requirement for the degree of Master of Science in (Mechatronics Engineering)." --On t.p. 
502 |a Thesis (MSMCT)--International Islamic University Malaysia, 2016. 
504 |a Includes bibliographical references (leaves 97-103). 
520 |a In social interaction, the explicit and implicit communication plays a significant role in an effective interaction. However, the typical modalities of interaction such as verbal and body language, sometimes, may be deterred causing meaningful communication could not be achieved especially when dealing with an emotionally-challenged subject. Hence, the apprehension of their emotional states is highly intrinsic. Progress has been made in affective computing using the Autonomic Nervous System (ANS) parameters for affect detection. Nevertheless, while a significant number of findings have been reported, most of the experimentations employed the invasive approaches where direct contact between subject and sensor was required. Even though the existence of research that utilised the non-invasive approach for affect detection is irrefutable, yet, the universality of such approach remains a much-debated question as it is believed to be varied based on gender, culture and age. All the previously mentioned methods suffer from a number of serious drawbacks when dealing with the subjects who are unable to express their emotions explicitly. Henceforth, the thermal imaging based affect recognition was devoted in this thesis to classify six prototypical emotions. The ability of thermal imaging to quantify the ANS parameters through contactless, non-invasive and non-intrusive manner is believed could circumvent the limitation of other approaches. In the proposed framework, the first stage involves the image acquisition and enhancement using Contrast Limited Adaptive Histogram Equalization (CLAHE). In the second phase, the second order statistical features were extracted using Gray Level Co-occurrence Matrix (GLCM) from four regions of interest (ROI); periorbital, supraorbital, mouth and nose. Lastly, the third phase classifies the respective emotions using the k-nearest neighbour (k-NN) algorithm with 10-folds cross-validation routine. The proposed model was found to outperform the existing models with 86.7% accuracy (mean accuracy of existing models = 73.63%). 
596 |a 1 
650 0 |a Human-computer interaction 
650 0 |a Human-machine systems 
650 0 |a Affect (Psychology)  |x Computer simulation 
655 7 |a Theses, IIUM local 
690 |a Dissertations, Academic  |x Department of Mechatronics Engineering  |z IIUM 
710 2 |a International Islamic University Malaysia.  |b Department of Mechatronics Engineering 
856 4 |u http://studentrepo.iium.edu.my/handle/123456789/4566  |z Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. 
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