An Improved and Portable Eye-Blink Duration Detection System to Warn of Driver Fatigue

Hsieh, Chin Shun; Tai, Cheng Chi

doi:10.1080/10739149.2013.796560

Cited by 34 publications

(17 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This difference is noticeable since it is about one‐quarter of the original blink duration (200 ms). Hsieh et al proposed a system that utilizes eye blink durations as one of the main schemes to warn drivers about fatigue. Schleicher et al stated that blink duration is by far the most important variable to indicate subjective, as well as video‐rated fatigue, and the second most important is the delay of reopening the eye.…”

Section: Results Of the Experimentsmentioning

confidence: 99%

A study on differences in human perception between a real and an AR scene viewed in an OST‐HMD

et al. 2019

View full text Add to dashboard Cite

With the recent growth in the development of augmented reality (AR) technologies, it is becoming important to study human perception of AR scenes. In order to detect whether users will suffer more from visual and operator fatigue when watching virtual objects through optical see‐through head‐mounted displays (OST‐HMDs), compared with watching real objects in the real world, we propose a comparative experiment including a virtual magic cube task and a real magic cube task. The scores of the subjective questionnaires (SQ) and the values of the critical flicker frequency (CFF) were obtained from 18 participants. In our study, we use several electrooculogram (EOG) and heart rate variability (HRV) measures as objective indicators of visual and operator fatigue. Statistical analyses were performed to deal with the subjective and objective indicators in the two tasks. Our results suggest that participants were very likely to suffer more from visual and operator fatigue when watching virtual objects presented by the OST‐HMD. In addition, the present study provides hints that HRV and EOG measures could be used to explore how visual and operator fatigue are induced by AR content. Finally, three novel HRV measures are proposed to be used as potential indicators of operator fatigue.

show abstract

Section: Results Of the Experimentsmentioning

confidence: 99%

A study on differences in human perception between a real and an AR scene viewed in an OST‐HMD

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Bulling et al have recently shown EOG metrics to be useful for recognizing different types of activities via eye movement patterns [19, 21]. There have been a number of studies attempting to measure fatigue solely through EOG metrics [29, 37, 46, 53, 60], but achieving high accuracy requires placing additional electrodes on the face to ensure high-quality data. Steps towards miniaturizing the sensors have been made in the literature [20].…”

Section: Related Workmentioning

confidence: 99%

iLid

Rostaminia

Mayberry

Ganesan

et al. 2017

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

View full text Add to dashboard Cite

The ability to monitor eye closures and blink patterns has long been known to enable accurate assessment of fatigue and drowsiness in individuals. Many measures of the eye are known to be correlated with fatigue including coarse-grained measures like the rate of blinks as well as fine-grained measures like the duration of blinks and the extent of eye closures. Despite a plethora of research validating these measures, we lack wearable devices that can continually and reliably monitor them in the natural environment. In this work, we present a low-power system, iLid, that can continually sense fine-grained measures such as blink duration and Percentage of Eye Closures (PERCLOS) at high frame rates of 100fps. We present a complete solution including design of the sensing, signal processing, and machine learning pipeline; implementation on a prototype computational eyeglass platform; and extensive evaluation under many conditions including illumination changes, eyeglass shifts, and mobility. Our results are very encouraging, showing that we can detect blinks, blink duration, eyelid location, and fatigue-related metrics such as PERCLOS with less than a few percent error.

show abstract

“…Eye blink frequency has been studied as a factor in fatigue and drowsiness detection systems to alert drivers. [1][2][3][4] In other research, 5 the eye fatigue measurement is researched in display with the assumption being that people blink more than usual when fatigued. 5 Although not associated with drowsiness or fatigue, there are many studies about eye blink.…”

Section: Introductionmentioning

confidence: 99%

Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

et al. 2015

View full text Add to dashboard Cite

The classification of eye openness and closure has been researched in various fields, e.g., driver drowsiness detection, physiological status analysis, and eye fatigue measurement. For a classification with high accuracy, accurate segmentation of the eye region is required. Most previous research used the segmentation method by image binarization on the basis that the eyeball is darker than skin, but the performance of this approach is frequently affected by thick eyelashes or shadows around the eye. Thus, we propose a fuzzy-based method for classifying eye openness and closure. First, the proposed method uses I and K color information from the HSI and CMYK color spaces, respectively, for eye segmentation. Second, the eye region is binarized using the fuzzy logic system based on I and K inputs, which is less affected by eyelashes and shadows around the eye. The combined image of I and K pixels is obtained through the fuzzy logic system. Third, in order to reflect the effect by all the inference values on calculating the output score of the fuzzy system, we use the revised weighted average method, where all the rectangular regions by all the inference values are considered for calculating the output score. Fourth, the classification of eye openness or closure is successfully made by the proposed fuzzy-based method with eye images of low resolution which are captured in the environment of people watching TV at a distance. By using the fuzzy logic system, our method does not require the additional procedure of training irrespective of the chosen database. Experimental results with two databases of eye images show that our method is superior to previous approaches.

show abstract

An Improved and Portable Eye-Blink Duration Detection System to Warn of Driver Fatigue

Cited by 34 publications

References 17 publications

A study on differences in human perception between a real and an AR scene viewed in an OST‐HMD

A study on differences in human perception between a real and an AR scene viewed in an OST‐HMD

iLid

Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

Contact Info

Product

Resources

About