2022
DOI: 10.28991/hij-2022-03-01-02
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Eye Tracking Algorithm Based on Multi Model Kalman Filter

Abstract: One of the most important pieces of Human Machine Interface (HMI) equipment is an eye tracking system that is used for many different applications. This paper aims to present an algorithm in order to improve the efficiency of eye tracking in the image by means of a multi-model Kalman filter. In the classical Kalman filter, one model is used for estimation of the object, but in the multi-model Kalman filter, several models are used for estimating the object. The important features of the multiple-model Kalman f… Show more

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Cited by 16 publications
(8 citation statements)
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“…Thus, the process from the stage of production to the stage of consumption can be made shorter [14]. In the agricultural industry, it is possible to increase efficiency and productivity by using this type of agricultural technology [15,16]. 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000…”
Section: Figure 1 Top Countries In Dates Production (Fao 2019) [10]mentioning
confidence: 99%
“…Thus, the process from the stage of production to the stage of consumption can be made shorter [14]. In the agricultural industry, it is possible to increase efficiency and productivity by using this type of agricultural technology [15,16]. 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000…”
Section: Figure 1 Top Countries In Dates Production (Fao 2019) [10]mentioning
confidence: 99%
“…Bagherzadeh andToosizadeh [12] Eye tracking systems are important components of Human Machine Interface (HMI) equipment, and this paper presents an algorithm for increasing eye tracking efficiency using multi-model Kalman filters.Multi-model Kalman filters employ multiple models for object estimation, aiming to boost efficiency and reduce estimation errors. Based on the typical behavior of the human eye, the algorithm first recognizes the initial eye position using the Support Vector Machine (SVM), and then uses a multi-model Kalman filter to predict the eye's position in the next frame using constant speed and acceleration models.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The performance of an aided navigation system is directly affected by optimal state estimation techniques used in the integration or sensor fusion scheme. Kalman Filter (KF) is the most widely used optimal state estimator in many theorical and industrial applications including integrated navigation systems (6)(7)(8)(9)(10)(11). To achieve an optimal solution in the KF, determining proper models for the system and stochastic noises is a key factor problem (12).…”
Section: Introductionmentioning
confidence: 99%