Facial expression based computer cursor control system for assisting physically disabled person

Maruthapillai, Vasanthan; Murugappan, M.; Nagarajan, R.; Ilias, B.; Letchumikanth, J.

doi:10.1109/comnetsat.2012.6380800

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…M. Vasanthan eta al. [36] discusses a mechanism to control a curser using different facial expressions. Ruoyu Hou discussed a novel mechanism of designing and implementing a power assisted wheel chair [37].…”

Section: Assistive Aids For Speech Disabledmentioning

confidence: 99%

Assistive aids for the disabled: Past, present and future

Chitranshi

Yadav

2014

2014 5th International Conference - Confluence the Next Generation Information Technology Summit (Confluence)

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Assistive aids have been made in the recent years to help the disabled. These include persons with visual, hearing, speech, locomotor and mental disabilities. If the technology continues to grow over the next few years the poor disabled population will have access to low cost assistive aids and may become more employable. This paper discusses the assistive aids that has been developed in the past, recent years, compares them and predicts the future assistive aids that will drive the technology for the disabled.

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Section: Assistive Aids For Speech Disabledmentioning

confidence: 99%

Assistive aids for the disabled: Past, present and future

Chitranshi

Yadav

2014

2014 5th International Conference - Confluence the Next Generation Information Technology Summit (Confluence)

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“…As the study on the recognition of the eye blinking, for example, [13] reports the method based on the blinking detection to assist the handicapped, who cannot move his body by himself freely, to communicate to another person. [14] uses illuminant markers to control the cursor movement in computer applications based on facial expressions such as cheek movement, eye brow, and mouth open. As the research to recognize the motion of the head, for example, [15] reports the method to operate the electric wheelchair with the interface that detects head gesture motion using depth sensor.…”

Section: Related Workmentioning

confidence: 99%

Cheek Tracking Interface for Limb-disabled Person

Noboru

Yoshida

2018

Proceedings of the 6th IIAE International Conference on Intelligent Systems and Image Processing 2018

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Computer interface for severely limb-disabled person is an important issue to investigate. Head, eye and mouse tracking are main sources of information for such interface. Since limb-disabled person cannot use under the neck, how to enrich information available is important. This paper tries to use mouse, more precisely cheek, information. Although recent progress of speech recognition technology realizes interfaces to control various machines accurately, the limb-disables who cannot speak cannot use such speech recognition interface. Computer interfaces need to be developed according to their degrees of disability and must use the body part which they can move effectively. There are many handicapped persons whose degrees of disability are different. It is desirable to prepare various computer interfaces. Such interfaces must use various body parts to cope with various handicaps. From above viewpoints, this paper proposes the use of the cheek visual appearance changes using web camera. The experimental results with two layer convolutional deep learning processing show that the average recognition accuracy is 97%. In addition, the effects of the image size and deep learning network structure for the recognition performance are reported in this paper.

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“…Abdat et al [6] have built a anthropometric model for facial feature points detection for facial expression recognition system. Vasanthan et al [7] have proposed facial expression based computer cursor control system for physically disabled person. A facial expression recognition from live video input using temporal cues is proposed by [8].…”

Section: Introductionmentioning

confidence: 99%

MP-FEG: Media Player controlled by Facial Expressions and Gestures

Agarwal

Umer

2015

2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

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In this paper we represent a new technique to interact with the computer in a non-tangible way. Specifically we have designed a Media Player system controller by Facial Expressions and Gestures (MP-FEG). We detect and track one landmark point on the finger and 18 landmark points on the lips to capture the movement of the finger and the lips of the user. The movement patterns are classified into hand gestures and facial expressions using support vector machine (SVM). We have achieved ∼98.65% and ∼100% recognition accuraciesfor hand-gestures and facial expressions respectively. Occurrence of each of these actions (5 hand-gesturs and 3 facial expressions) is associated with a command to control (e.g., to select, play, pause the video) the video player. Perceptional quality analysis by user survey rates the experience of the non-tangible human-computerinteraction facilited by the proposed technique as 'good'.

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Facial expression based computer cursor control system for assisting physically disabled person

Cited by 11 publications

References 9 publications

Assistive aids for the disabled: Past, present and future

Assistive aids for the disabled: Past, present and future

Cheek Tracking Interface for Limb-disabled Person

MP-FEG: Media Player controlled by Facial Expressions and Gestures

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