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Evaluation of Fear Using Nonintrusive Measurement of Multimodal Sensors.

Choi JS, Bang JW, Heo H, Park KR - Sensors (Basel) (2015)

Bottom Line: Further, the latter causes inconvenience to the user due to the sensors attached to the body.Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies.Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. jjongssuk@dgu.edu.

ABSTRACT
Most previous research into emotion recognition used either a single modality or multiple modalities of physiological signal. However, the former method allows for limited enhancement of accuracy, and the latter has the disadvantages that its performance can be affected by head or body movements. Further, the latter causes inconvenience to the user due to the sensors attached to the body. Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies. Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors. Experimental results based on the t-test, the effect size and the sum of all of the correlation values with other modalities showed that facial temperature and subjective evaluation are more reliable than electroencephalogram (EEG) and eye blinking rate for the evaluation of fear.

No MeSH data available.


Related in: MedlinePlus

Experiment for measuring the accuracy of the geometric transform. The top and bottom figures of (a–c) are images from the visible-light and thermal cameras, respectively. The NIR illuminator is positioned at example positions: (a) Position 1, (b) Position 5 and (c) Position 9.
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sensors-15-17507-f011: Experiment for measuring the accuracy of the geometric transform. The top and bottom figures of (a–c) are images from the visible-light and thermal cameras, respectively. The NIR illuminator is positioned at example positions: (a) Position 1, (b) Position 5 and (c) Position 9.

Mentions: In the first experiment, we measured the accuracy of the calibration of the visible-light and thermal cameras. As explained in Section 2.2 and shown in Figure 5, four NIR illuminators at the four corner positions are used for obtaining the matrix of the geometric transform. Then, we measured the accuracy of the geometric transform using additional NIR illuminators at nine other positions (other than the four corner positions). Figure 11 shows three example cases of NIR illuminator location.


Evaluation of Fear Using Nonintrusive Measurement of Multimodal Sensors.

Choi JS, Bang JW, Heo H, Park KR - Sensors (Basel) (2015)

Experiment for measuring the accuracy of the geometric transform. The top and bottom figures of (a–c) are images from the visible-light and thermal cameras, respectively. The NIR illuminator is positioned at example positions: (a) Position 1, (b) Position 5 and (c) Position 9.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541947&req=5

sensors-15-17507-f011: Experiment for measuring the accuracy of the geometric transform. The top and bottom figures of (a–c) are images from the visible-light and thermal cameras, respectively. The NIR illuminator is positioned at example positions: (a) Position 1, (b) Position 5 and (c) Position 9.
Mentions: In the first experiment, we measured the accuracy of the calibration of the visible-light and thermal cameras. As explained in Section 2.2 and shown in Figure 5, four NIR illuminators at the four corner positions are used for obtaining the matrix of the geometric transform. Then, we measured the accuracy of the geometric transform using additional NIR illuminators at nine other positions (other than the four corner positions). Figure 11 shows three example cases of NIR illuminator location.

Bottom Line: Further, the latter causes inconvenience to the user due to the sensors attached to the body.Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies.Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea. jjongssuk@dgu.edu.

ABSTRACT
Most previous research into emotion recognition used either a single modality or multiple modalities of physiological signal. However, the former method allows for limited enhancement of accuracy, and the latter has the disadvantages that its performance can be affected by head or body movements. Further, the latter causes inconvenience to the user due to the sensors attached to the body. Among various emotions, the accurate evaluation of fear is crucial in many applications, such as criminal psychology, intelligent surveillance systems and the objective evaluation of horror movies. Therefore, we propose a new method for evaluating fear based on nonintrusive measurements obtained using multiple sensors. Experimental results based on the t-test, the effect size and the sum of all of the correlation values with other modalities showed that facial temperature and subjective evaluation are more reliable than electroencephalogram (EEG) and eye blinking rate for the evaluation of fear.

No MeSH data available.


Related in: MedlinePlus