Name
Abstract | ||
|---|---|---|
In this paper, we show the feasibility of using high-speed video for measurement of startle eyeblinks as a new augmentative modality for biometric security, as blinks can reveal emotional states of interest in security screenings using nonintrusive measurements. Using neural network as classifiers, this initial study shows that upper eyelid tracking at 250 frames per second can categorize startle blinks with accuracies comparable to those of the well-established but intrusive EMG-based measures of muscles in charge of eyelid closure. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IJCNN.2009.5179040 | IJCNN |
Keywords | Field | DocType |
high-speed video,emotional state,neural network,security screening,intrusive emg-based measure,biometric security,startle eyeblinks,eyelid closure,initial study,startle eyeblink metrics,upper eyelid tracking,biometrics,neural networks,feature extraction,image processing,neural nets,signal analysis,psychology,psychometrics,data mining,artificial neural networks,signal detection,electrodes,frames per second | Categorization,Detection theory,Pattern recognition,Computer science,Image processing,Feature extraction,Speech recognition,Artificial intelligence,Frame rate,Biometrics,Artificial neural network,Eyelid closure | Conference |
ISSN | Citations | PageRank |
2161-4393 | 3 | 0.47 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christopher T. Lovelace | 1 | 7 | 0.98 |
| Reza Derakhshani | 2 | 166 | 21.08 |
| Sriram Pavan Kumar Tankasala | 3 | 3 | 0.47 |
| Diane L. Filion | 4 | 3 | 1.15 |