A Video Processing Based Eye Gaze Recognition Algorithm for Wheelchair Control

Rupanagudi, Sudhir Rao; Bhat, Varsha G.; Gurikar, Shreya K.; Koundinya, Sriharsha; Kumar, Mohit; Shreyas, R.; Shilpa, S; Suman, Nupur; Bademi, Rachana R.; Koppisetti, Manisha; Satyananda, Vasanthi

doi:10.1109/dessert.2019.8770025

Cited by 12 publications

(10 citation statements)

References 27 publications

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“…The authors in [11] uses machine learning to extract the iris by segmentation algorithm. All experiments were implemented using the MATLAB software, the algorithm accuracy reached to 86% which is not satisfactory, also the authors mentioned that the speed of detection increased but did not mention its value.…”

Section: Related Workmentioning

confidence: 99%

Wheelchair Control System based Eye Gaze

Amer¹,

Ramadan²,

Kamh³

et al. 2021

IJACSA

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The inability to control the limbs is the main reason that affects the daily activities of the disabled which causes social restrictions and isolation. More studies were performed to help disabilities for easy communication with the outside world and others. Various techniques are designed to help the disabled in carrying out daily activities easily. Among these technologies is the Smart Wheelchair. This research aims to develop a smart eye-controlled wheelchair whose movement depends on eye movement tracking. The proposed Wheelchair is simple in design and easy to use with low cost compared with previous Wheelchairs. The eye movement was detected through a camera fixed on the chair. The user's gaze direction is obtained from the captured image after some processing and analysis. The order is sent to the Arduino Uno board which controls the wheelchair movement. The Wheelchair performance was checked using different volunteers and its accuracy reached 94.4% with a very short response time compared with the other existing chairs.

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Section: Related Workmentioning

confidence: 99%

Wheelchair Control System based Eye Gaze

Amer¹,

Ramadan²,

Kamh³

et al. 2021

IJACSA

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“…𝐄𝐫𝐫𝐨𝐫 𝐢𝐧 𝐝𝐢𝐬𝐭𝐚𝐧𝐜𝐞 = 𝐭𝐨𝐭𝐚𝐥 𝐝𝐞𝐥𝐚𝐲 𝐢𝐧 𝐭𝐡𝐞 𝐬𝐲𝐬𝐭𝐞𝐦 * 𝐬𝐩𝐞𝐞𝐝 𝐨𝐟 𝐭𝐡𝐞 𝐰𝐡𝐞𝐞𝐥𝐜𝐡𝐚𝐢𝐫 (8) By knowing the travelling time of the signal, the distance can be calculated using Equation (7). Being analogous to the radars' operation, the time should be divided by two because the waves travel the distance twice.…”

Section: Safety System-ultrasonic Sensorsmentioning

confidence: 99%

“…The total delay in the system is the sum of delay introduced by the MCU and that of the sensor. The delay of the sensor strictly cannot exceed 1 millisecond because the average distance the sensor can measure is ~1.75 m. The average time of travelling of the ultrasonic wave can be calculated using Equation (7). The delay that may occur due to the MCU processing, it is in microseconds range.…”

Section: Safety System-ultrasonic Sensorsmentioning

confidence: 99%

“…Research for eye tracking techniques has been progressively implemented in many applications, such as driving fatigue-warning systems [2,3], mental health monitoring [4,5], eye-tracking controlled wheelchair [6,7], and other human-computer interface systems. However, there are several constraints such as reliable real-time performance, high accuracy, availability of components, and having a portable and non-intrusive system [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control

Dahmani

Chowdhury

Khandakar

et al. 2020

Sensors

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In the 34 developed and 156 developing countries, there are ~132 million disabled people who need a wheelchair, constituting 1.86% of the world population. Moreover, there are millions of people suffering from diseases related to motor disabilities, which cause inability to produce controlled movement in any of the limbs or even head. This paper proposes a system to aid people with motor disabilities by restoring their ability to move effectively and effortlessly without having to rely on others utilizing an eye-controlled electric wheelchair. The system input is images of the user’s eye that are processed to estimate the gaze direction and the wheelchair was moved accordingly. To accomplish such a feat, four user-specific methods were developed, implemented, and tested; all of which were based on a benchmark database created by the authors. The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. CNN exhibited the best performance (i.e., 99.3% classification accuracy), and thus it was the model of choice for the gaze estimator, which commands the wheelchair motion. The system was evaluated carefully on eight subjects achieving 99% accuracy in changing illumination conditions outdoor and indoor. This required modifying a motorized wheelchair to adapt it to the predictions output by the gaze estimation algorithm. The wheelchair control can bypass any decision made by the gaze estimator and immediately halt its motion with the help of an array of proximity sensors, if the measured distance goes below a well-defined safety margin. This work not only empowers any immobile wheelchair user, but also provides low-cost tools for the organization assisting wheelchair users.

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“…Segmentation Since the objects of interest appear the brightest, manual thresholding can be applied to segment the exudates and optic disc. A threshold (t) of 240 is set to make sure that all bright objects are extracted, as represented in equation (10) [45]. Figure 3b shows segmented image.…”

Section: Distance Tranformmentioning

confidence: 99%

Hard Exudate Extraction from Fundus Images using Watershed Transform

Satyananda

Narayanaswamy

Karibasappa

2019

IJEEI

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Diabetic Retinopathy is a medical condition which affects the eyes due to increased blood sugar levels. This is characterized by presence of exudatesdeposits of lipids in the posterior pole of the retina. If this ailment is not treated in earlier stages these deposits can cause blurred vision or even permanent blindness. This paper concentrates on extraction of hard exudates and optic disc from the retinal images of eyes using Marker based Watershed approach, which uses the minima imposition method to create mask and marker. The varying contrast across all the images has been taken care by a non-linear equation. Once these bright objects have been extracted from fundus images, area estimation is performed to eliminate the optic disk, thus retaining only exudates. These images have been procured from publicly available databases. Though software systems are easy to install, they prove to be expensive in terms of time and cost; thus this method has also been implemented on FPGA for an on-chip solution. The precision and sensitivity for exudate extraction sans optic disk are found to be 92.4% and 83.78% respectively. Though other techniques exist which provide better accuracy, the method described in this paper is found to be hardware friendly in comparison with other proven methods. Few steps of the algorithm developed are implemented on FPGA to provide an embedded system approach to this work, considering the advantages of a hardware-software combination.

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A Video Processing Based Eye Gaze Recognition Algorithm for Wheelchair Control

Cited by 12 publications

References 27 publications

Wheelchair Control System based Eye Gaze

Wheelchair Control System based Eye Gaze

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control

Hard Exudate Extraction from Fundus Images using Watershed Transform

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