Gaze and Eye Tracking: Techniques and Applications in ADAS

Khan, Muhammad Qasim; Lee, Sukhan

doi:10.3390/s19245540

Cited by 79 publications

(46 citation statements)

References 190 publications

(252 reference statements)

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“…Another potentially useful area to investigate for integration would be in advanced driving assistance systems (ADAS), such as in driverless vehicles. Both emotion recognition and eye-tracking have been investigated in ADAS [107] but as separate systems, hence integrating both approaches would likely be beneficial. Another potentially useful area to investigate would be in smart home applications.…”

Section: Devices and Applicationsmentioning

confidence: 99%

Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges

Lim

Mountstephens

Teo

2020

Sensors

180

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The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality.

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Section: Devices and Applicationsmentioning

confidence: 99%

Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges

Lim

Mountstephens

Teo

2020

Sensors

180

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“…Calibration can be challenging for this equipment when trial sessions are long, contact or corrective lenses are used, or there are long eye lashes [14]. Modern videography and computer algorithms can measure parameters using reflections from eye layers and appearance based techniques using facial feature recognition [15]. These are discussed in more detail in the section on Advanced Driving Assistance Systems (ADAS).…”

Section: Tracking Methodsmentioning

confidence: 99%

“…Due to the frequency of crashes, there is a growing desire to reduce visual scanning errors and their causes. It is estimated that motor vehicle crashes account for over 1,000,000 deaths and 20,000,000 injuries per year globally, with costs that may represent 2% of a country's GNP [15]. A significant reduction in crashes using facial feature recognition with ADAS technology is a major goal of many manufacturers.…”

Section: Eye Tracking In Advanced Driving Assistance Systems (Adas)mentioning

confidence: 99%

The Role of Eye Tracking Technology in Assessing Older Driver Safety

Carr

Grover

2020

Geriatrics

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A growing body of literature is focused on the use of eye tracking (ET) technology to understand the association between objective visual parameters and higher order brain processes such as cognition. One of the settings where this principle has found practical utility is in the area of driving safety. Methods: We reviewed the literature to identify the changes in ET parameters with older adults and neurodegenerative disease. Results: This narrative review provides a brief overview of oculomotor system anatomy and physiology, defines common eye movements and tracking variables that are typically studied, explains the most common methods of eye tracking measurements during driving in simulation and in naturalistic settings, and examines the association of impairment in ET parameters with advanced age and neurodegenerative disease. Conclusion: ET technology is becoming less expensive, more portable, easier to use, and readily applicable in a variety of clinical settings. Older adults and especially those with neurodegenerative disease may have impairments in visual search parameters, placing them at risk for motor vehicle crashes. Advanced driver assessment systems are becoming more ubiquitous in newer cars and may significantly reduce crashes related to impaired visual search, distraction, and/or fatigue.

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“…Finally, once these images are fed as inputs into a 3D convolutional neural network and a 2D convolutional neural network, respectively, the model is able to perform action recognition. Other approaches focused on the transport domain, such as [ 21 , 22 , 23 , 24 ], rely on facial expressions and behavior, gaze and eye tracking for detecting emotions, stress, anxiety, and panic. Although effective, those methods add another layer of complexity to our solution, as they require high resolution facial images which subsequently introduce privacy issues.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Abnormal Event Detection for Enhanced Security in Autonomous Shuttles Mobility Infrastructures

Tsiktsiris

Dimitriou

Lalas

et al. 2020

Sensors

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Autonomous vehicles (AVs) are already operating on the streets of many countries around the globe. Contemporary concerns about AVs do not relate to the implementation of fundamental technologies, as they are already in use, but are rather increasingly centered on the way that such technologies will affect emerging transportation systems, our social environment, and the people living inside it. Many concerns also focus on whether such systems should be fully automated or still be partially controlled by humans. This work aims to address the new reality that is formed in autonomous shuttles mobility infrastructures as a result of the absence of the bus driver and the increased threat from terrorism in European cities. Typically, drivers are trained to handle incidents of passengers’ abnormal behavior, incidents of petty crimes, and other abnormal events, according to standard procedures adopted by the transport operator. Surveillance using camera sensors as well as smart software in the bus will maximize the feeling and the actual level of security. In this paper, an online, end-to-end solution is introduced based on deep learning techniques for the timely, accurate, robust, and automatic detection of various petty crime types. The proposed system can identify abnormal passenger behavior such as vandalism and accidents but can also enhance passenger security via petty crimes detection such as aggression, bag-snatching, and vandalism. The solution achieves excellent results across different use cases and environmental conditions.

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Gaze and Eye Tracking: Techniques and Applications in ADAS

Cited by 79 publications

References 190 publications

Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges

Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges

The Role of Eye Tracking Technology in Assessing Older Driver Safety

Real-Time Abnormal Event Detection for Enhanced Security in Autonomous Shuttles Mobility Infrastructures

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