可見光眼動儀以虹膜定位作為判斷眼睛凝視方向的主要基準。相較於傳統紅外光眼動儀，可見光眼動儀無法在影像中找出完整的瞳孔位置，必須以虹膜邊界來估算瞳孔中心。然而，由於虹膜邊界可能被眼瞼遮蓋，因此需要仰賴可靠的眼球模型與虹膜邊界比對演算法來精確定位虹膜位置。
在過去的幾年中，研究團隊已提出一種有效率的階層式搜尋法，用於在眼睛照片中定位虹膜邊界，並據以估計視線方向。本論文以此演算法架構為基礎，提出了可見光眼動儀中虹膜匹配的晶片架構，使其能夠從照片的特定範圍中快速完成虹膜匹配。在可用硬體資源受限的情況下，巧妙運用平行計算與管線式處理，以提高本晶片的計算效率。並在FPGA上實作了此晶片架構，其效能與處理結果與多核心的電腦計算結果相近，成功實現即時處理的目標。

The visible-spectrum eye tracker relies on iris positioning as the main feature for determining the direction of gaze. In comparison to traditional infrared eye trackers, the visible-spectrum eye tracker cannot identify the complete pupil position in the image and must estimate the pupil center based on the limbus circle. However, since the limbus circle may be obscured by eyelids, it is necessary to build a reliable eyeball model and to implement a limbus circle matching algorithm for precise iris positioning.
Over the past few years, the research team has proposed an efficient hierarchical search method for locating the limbus circle in eye images and subsequently estimating the gaze direction. Building upon this algorithmic framework, this paper introduces a chip architecture for limbus circle matching in visible-spectrum eye trackers, enabling rapid limbus circle matching within specific regions of photos. To enhance computational efficiency within hardware resource constraints, parallel computing and pipeline processing are appropriately applied in the chip design. The proposed chip architecture has been implemented on an FPGA, demonstrating performance and processing results comparable to those of multi-core computer calculations and achieving real-time processing goals.

E. Guestrin and M. Eizenman, “General theory of remote gaze estimation using the
pupil center and corneal reflections,” IEEE Transactions on Biomedical Engineering,
vol. 53, no. 6, pp. 1124–1133, 2006.

S.-J. Baek, K.-A. Choi, C. Ma, Y.-H. Kim, and S.-J. Ko, “Eyeball model-based iris center localization for visible image-based eye-gaze tracking systems,” IEEE Transactions on Consumer Electronics, vol. 59, no. 2, pp. 415–421, 2013.

W.-C. Kao and S.-C. Lin, “Iris region matching for visible-spectrum gaze trackers,”
in 2020 IEEE International Conference on Consumer Electronics (ICCE), 2020, pp. 1–2.

W.-C. Kao and Y.-C. Chiu, “Hierarchical search of optimal limbus circle matching
for gaze tracking systems,” in 2017 IEEE 7th International Conference on Consumer
Electronics - Berlin (ICCE-Berlin), 2017, pp. 233–234.

Y.-H. Zou, J. Wen, H.-Y. Xing, and Y. Zhu, “Rapid eye movement tracking method
based on fpga,” in 2016 International Conference on Machine Learning and Cybernetics (ICMLC), vol. 2, 2016, pp. 1021–1025.

D. A. Padilla, J. A. B. Adriano, J. R. Balbin, I. G. Matala, J. J. R. Nicolas, and S. R. R. Villadelgado, “Implementation of eye gaze tracking technique on fpgabased on-screen keyboard system using verilog and matlab,” in TENCON 2017 - 2017 IEEE Region 10 Conference, 2017, pp. 2771–2776.

K. Gayathri, S. Harshiniv, and K. Dr Senthil Kumar, “Hardware implementation of
sorting algorithm using fpga,” IJARIIE-ISSN (O)-2395-4396, vol. 4, no. 2, 2018.

K. E. Batcher, “Sorting networks and their applications,” in Proceedings of the April 30–May 2, 1968, spring joint computer conference, 1968, pp. 307–314.

W.-C. Kao and Y.-C. Chiu, “Eyeball model construction and matching for visiblespectrum gaze tracking systems,” in 2018 IEEE 8th International Conference on Consumer Electronics - Berlin (ICCE-Berlin), 2018, pp. 1–2.

H. Qin, X. Xu, Z. Hu, and D. Zhang, “Eye tracking system based on sopc,” in 2014
21st IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2014, pp. 171–174.

B.-C. Chen, P.-C. Wu, and S.-Y. Chien, “Real-time eye localization, blink detection,
and gaze estimation system without infrared illumination,” in 2015 IEEE International Conference on Image Processing (ICIP), 2015, pp. 715–719.