在現今的基於內容的圖像檢索的研究中，會將人的主觀認知考慮進去。因為傳統的圖像檢索中採取低階特徵來找出圖片上可能的重要區域的方法和人的感覺還是有著相當大的語意上的鴻溝。然而藉由考慮人對圖片的主觀認知，可以讓人找到對它而言圖片上重要的部分，再去做圖像檢索，找出使用者想要的圖片。這樣的作法是比較自然且直觀的。還能達到個人化的效果，因為每個人對同一張圖片上覺得重要的物體可能不盡相同。在本論文中的圖像檢索系統採用眼動軌跡當作人的主觀認知來輔助檢索。因為在心理學的研究中有提到，人在看圖片的時候會有較多的凝視點落在他覺得重要的區域上。所以藉由這個理論，本論文利用使用者看圖片的眼動軌跡即時的調整圖片上物體的重要性。最後將重要性高的數個物體去做圖像檢索，找出含有這些對這個使用者是重要的物體的圖片。經由實驗證實，眼動軌跡輔助圖像檢索的確可以減少不重要的物體對圖像檢索的干擾，繼而可以提升圖像檢索系統的效能。 / Recently, researches in Content-Based Image Retrieval (CBIR) focuses on incorporation of knowledge about human perception in the systems’ design and implementation process. This enables the design of more natural and intuitive image retrieval techniques in order to overcome some of the challenges faced by modern CBIR system such as the difficulty to extract important regions of an image. By researches of psychology, user’s eye tracking reflects his interest. So, in my CBIR system, user’s eye movements were used online to adjust the importance for objects in query image. Thus in my system, only those images with important objects will be retrieved. One experiment was performed: record the eye movement of participants on query images. Then compare my approach with a classic CBIR system according to performance. The results reveal that higher retrieval performance of my image retrieval system because of decreasing the influence of not importance objects to image retrieval system.