Event-Based Eye Tracking. AIS 2024 Challenge Survey

This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting the pupil center of the eye. The challenge emphasizes efficient eye tracking with event cameras to achieve good task accu...

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Hauptverfasser:	Wang, Zuowen, Gao, Chang, Wu, Zongwei, Conde, Marcos V, Timofte, Radu, Liu, Shih-Chii, Chen, Qinyu, Zha, Zheng-jun, Zhai, Wei, Han, Han, Liao, Bohao, Wu, Yuliang, Wan, Zengyu, Wang, Zhong, Cao, Yang, Tan, Ganchao, Chen, Jinze, Pei, Yan Ru, Brüers, Sasskia, Crouzet, Sébastien, McLelland, Douglas, Coenen, Oliver, Zhang, Baoheng, Gao, Yizhao, Li, Jingyuan, So, Hayden Kwok-Hay, Bich, Philippe, Boretti, Chiara, Prono, Luciano, Lică, Mircea, Dinucu-Jianu, David, Grîu, Cătălin, Lin, Xiaopeng, Ren, Hongwei, Cheng, Bojun, Zhang, Xinan, Vial, Valentin, Yezzi, Anthony, Tsai, James
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition
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Beschreibung
Zusammenfassung:	This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting the pupil center of the eye. The challenge emphasizes efficient eye tracking with event cameras to achieve good task accuracy and efficiency trade-off. During the challenge period, 38 participants registered for the Kaggle competition, and 8 teams submitted a challenge factsheet. The novel and diverse methods from the submitted factsheets are reviewed and analyzed in this survey to advance future event-based eye tracking research.
DOI:	10.48550/arxiv.2404.11770