Gaze and blinking base human machine interaction system

Mange, Ashutosh A.; Choudhari, Anagha V.; Prasad, Shyam Sunder

doi:10.1109/iccic.2015.7435729

Cited by 5 publications

(2 citation statements)

References 31 publications

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“…IR-OG has been employed as a method of AAC for people with disabilities by filtering natural blinking and converting voluntary blinks into computer events such as mouse clicks [44], [64] or a communication code (e.g. Morse) [57].…”

Section: A Ir-ogmentioning

confidence: 99%

Communication Technologies Based on Voluntary Blinks: Assessment and Design

et al. 2019

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Some people with severe disabilities are confined in a state in which communication is virtually impossible, being reduced to communicating with their eyes or using sophisticated systems that translate thoughts into words. The EyeTrackers and Brain-Computer Interfaces (BCIs) are suitable systems for those people but their main drawback is their cost. More affordable devices are capable of detecting voluntary blinks and translating them into a binary signal that allows the selection, for example, of an ideogram on a communication board. We tested four different systems based on infrared, bioelectrical signals (Electro-Oculography (EOG) and Electro-Encephalography (EEG)), and video processing. The experiments were performed by people with/without disabilities and analyzed the systems' performances, usability, and method of voluntary blinking (long blinks or sequence of two short blinks). The best accuracy (99.3%) was obtained using Infrared-Oculography (IR-OG) and the worst with the EEG headset (85.9%) and there was a statistical influence of the technology on accuracy. Regarding the method of voluntary blinking, the use of long or double blinks had no statistical influence on accuracy, excluding EOG, and the time taken to perform double blinks was shorter, resulting in a potentially much faster interface. People with disabilities obtained similar values but with greater variability. The preferred technology and blinking methods were Video-Oculography (VOG) and long blinks, respectively. The several Open-Source Hardware (OSHW) devices have been developed and a new algorithm for detecting voluntary blinks has also been proposed, which outperforms most of the published papers in the reviewed literature.

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Section: A Ir-ogmentioning

confidence: 99%

Communication Technologies Based on Voluntary Blinks: Assessment and Design

et al. 2019

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“…Bu sebeple; insan-makine etkileşiminde, insana ait ifadeleri anlama, algılama ve modellemede sözsüz iletişimden sıkça yararlanılmaktadır. Parmak izi tanıma [3], göz hareketi ve iris tanıma [4], el-yazısı tanıma [5], tuş vuruşu tanıma [6], hareket tanıma [7], el işareti tanıma [8], yüz tanıma [9] gibi sistemler bunlara örnek olarak verilebilir. Yüz tanıma, bireye dışarıdan herhangi bir müdahale olmadan kişisel kimliğini doğrulama ve modellemeye imkân sağlayan bir yöntemdir [10].…”

Section: Gi̇ri̇ş (Introduction)unclassified

Bilgisayar Kullanıcılarına Yönelik Duygusal İfade Tespiti

Ayvaz¹,

Gürüler²

2017

Bilişim Teknolojileri Dergisi

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Özet-Bilgisayar kullanımının yaygınlaştığı günümüzde, insan-bilgisayar etkileşimi ile ilgili yenilikçi çalışmalar hız kazanmıştır. Bu yeniliklerden bir tanesi de bilgisayar kullanıcısı bireylerin duygusal durumlarının, makine ile öğrenilmesidir. Ofis ortamlarında bilgisayarla çalışan bireylerin duygu durumlarının tespit edilebilmesi, özellikle bu kişilerin moral durumu ile iş performansı ilişkisi hakkında anlamlı bilgiler sunabilir. Bu fikirden hareketle, bilgisayar kullanıcısının yüz ifadelerine dayalı anlık duygu tespiti gerçekleştiren prototip bir sistem geliştirilmiştir. Geliştirilen bu sistem sırasıyla; yüz tespiti, yüz işaretçilerinin tespiti, yüz işaretçilerine dayalı özniteliklerden oluşan eğitim veri setinin oluşturulması ve kural-tabanlı sınıflandırıcı ile anlık duygusal durum tespitini gerçekleştirmektedir. Çalışmanın özgünlüğünü ifade eden özniteliklerin ayırt edici karakteristiğini anlamak amacıyla mevcut eğitim veri seti destek vektör makineleri ile durağan bir şekilde sınıflandırılmıştır. Sonuç olarak, sistemin başarımı 10-katlı çapraz doğrulama ile %96,1 olarak tespit edilmiştir. Anahtar Kelimeler-İnsan-bilgisayar etkileşimi, duygusal ifade tespiti, veri madenciliği The Detection of Emotional Expression towards Computer UsersAbstract-In these days, with the widespread use of computers, innovative studies in human-computer interaction have accelerated. One of these innovations is to learn one"s emotional states with the help of a machine. Ascertaining the emotional states of a person working in the office environment can present meaningful information about the correlation between his/her morale and work performance. Based on this idea, an emotion detection system has been developed as a prototype. This system initially performs face and facial landmark detections. Training data set is prepared using these landmarks and then rule-based classifier detects instant emotional states. The training data set has been classified statically with support vector machines to understand the distinctive characteristics of the attributes that express the originality of this study. As a result, the success of the system was detected 96.1% with 10-fold crossvalidation.

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A Robust Webcam-based Eye Gaze Estimation System for Human-Computer Interaction

Roy¹,

Chanda²

2022

2022 International Conference on Innovations in Science, Engineering and Technology (ICISET)

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Gaze and blinking base human machine interaction system

Cited by 5 publications

References 31 publications

Communication Technologies Based on Voluntary Blinks: Assessment and Design

Communication Technologies Based on Voluntary Blinks: Assessment and Design

Bilgisayar Kullanıcılarına Yönelik Duygusal İfade Tespiti

A Robust Webcam-based Eye Gaze Estimation System for Human-Computer Interaction

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