TY - GEN
T1 - Research on Eye Tracking Process Optimization Based on Combined Kalman Filtering
AU - Zhang, Shuoyang
AU - Niu, Hongwei
AU - Hao, Jia
AU - Yao, Liya
AU - Wang, Yuekang
AU - Yang, Xiaonan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The application of eye tracking is becoming increasingly widespread and significant in daily life. However, due to physiological and technological limitations, eye tracking often contains noise and inaccuracies, which poses a challenge to its efficient use. This study aims to enhance the accuracy and precision of eye tracking, thereby improving the performance of human-computer interaction systems. We explore the application effects of various algorithms on eye-tracking data processing, including the Simple Moving Average, Weighted Moving Average, Exponential Weighted Moving Average, Kalman Filter Algorithm, and Combined Kalman Filter Algorithm. The advantages and disadvantages of these five algorithms are analyzed using eye-tracking data evaluation metrics focused on accuracy and precision. The findings of this study have practical application value in fields requiring high-precision eye movement data.
AB - The application of eye tracking is becoming increasingly widespread and significant in daily life. However, due to physiological and technological limitations, eye tracking often contains noise and inaccuracies, which poses a challenge to its efficient use. This study aims to enhance the accuracy and precision of eye tracking, thereby improving the performance of human-computer interaction systems. We explore the application effects of various algorithms on eye-tracking data processing, including the Simple Moving Average, Weighted Moving Average, Exponential Weighted Moving Average, Kalman Filter Algorithm, and Combined Kalman Filter Algorithm. The advantages and disadvantages of these five algorithms are analyzed using eye-tracking data evaluation metrics focused on accuracy and precision. The findings of this study have practical application value in fields requiring high-precision eye movement data.
KW - Accuracy
KW - Eye Tracking
KW - Kalman Filter Algorithm
KW - Precision
UR - http://www.scopus.com/inward/record.url?scp=85196111838&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-60449-2_16
DO - 10.1007/978-3-031-60449-2_16
M3 - Conference contribution
AN - SCOPUS:85196111838
SN - 9783031604485
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 228
EP - 239
BT - Human-Computer Interaction - Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
A2 - Kurosu, Masaaki
A2 - Hashizume, Ayako
PB - Springer Science and Business Media Deutschland GmbH
T2 - Human Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024
Y2 - 29 June 2024 through 4 July 2024
ER -