隨著科技的進步越來越重視使用者體驗，人們可透過眼動儀觀察眼睛凝視位置，了解整個視覺歷程與行為脈絡，以更貼近使用者真實感受與體驗。眼動儀的應用範圍包括3C產品、數位廣告及醫療生技。目前市面上的眼動儀是以紅外線光源達到眼睛視線的追蹤，然而長時間的紅外線照射會對眼睛帶來相當大的傷害。因此，近來有許多研究開始專研如何利用自然光源以取代紅外線照射對眼球的不良影響。

本研究目的是強調利用自然光源照射原理達到眼睛視線的追蹤。這款眼動儀系統主要是架構在外觀法的基礎上並強化其模型匹配的精準度，同時也使用形狀法加強模型建立的穩健性。此外，本研究成功導入頭部移動補償，有效彌補外觀法的缺點。在系統速度上，則加入粒子群聚演算法提升系統的運作速度。因此，本研究開發的眼動儀系統精準度高達1.17度，系統的處理速度為每秒250個畫面。

Due to the advancement of technology, eye trackers are used to help us understand human behavior and improve overall user experience. The gaze tracking systems are used in wide range of applications such as electronic devices, digital advertising, and medical biotechnology. Most gaze tracking systems use an infrared light source to track gaze positions, however, long hours of infrared light exposure may cause eye hurt. As a result, recent researches are focusing on how to replace infrared light source with visible light.

The aim of this research is to develop gaze tracking systems which use visible light to track user’s gaze positions. This gaze tracking system adopts appearance-based method to improve the accuracy of iris recognition. In addition, we use shape-based method for head movement compensation which not only enhances the robustness but also increases the accuracy of gaze tracking systems. Besides, the particle swarm optimization is applied to gaze tracking systems to reduce the processing time. Therefore, our system can achieve 1.17 high degree of accuracy and quick processing speed of 250 frames per second

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