本論文敘述對於智慧型個人數位相片管理瀏覽平台之研究、設計與實作過程。系統設計上基於整合多重證據架構，採用影像內容與使用者瀏覽行為之分析作為自動分類，判斷影像重要性與推薦程度的依據。影像自動分類方面，包括外部給予的標準資訊-EXIF資訊與分析影像內容，以其中人物存在數量與面積比例為依據的影像分類。而在影像的推薦方面，則採用影像品質之分析-包括對焦品質分析、曝光品質分析-與分析使用者瀏覽相片時的行為-包括停留時間與專注程度的整合為分析重要程度依據；最後則採用多模式(Multi-Modal)架構整合不同的評估結果並作為推薦的結論。 / In this thesis, we present the design and implementation of an intelligent personal digital photo browsing platform. The proposed system relies on multiple evidences inferred from image content as well as user behavior. Specifically, external EXIF data and face detection results are utilized to coarsely classify the digital images. Measures of image quality, including clarity and contrast, are calculated to further refine the search result. Moreover, we use web cameras to record and analyze the viewing behavior of the user and attempt to correlate the interest of the viewer to the effective viewing time. Finally, a multi-modal system is put in place to integrate the clues acquired from different modules.