影像內容檢索需求與使用之研究

近年來數位影像資訊的快速累積，使得影像的搜尋技術越來越受重視。以影像內容特徵進行查詢比對的影像內容檢索(content-Based Image Retrieval)已成為一項重要的影像檢索方式。本研究旨在探討使用者對於影像資訊的需求和尋求，以及使用者利用影像內容檢索系統進行查詢時的檢索情形和認知情況。本研究以使用者觀察為基礎，對38位受試者使用IBM發展的QBIC影像檢索系統，依深入訪談法、觀察法與有聲思考法，進行資料的蒐集。分析所得資料後，比較重要的結論歸納如下：(1)影像資訊的需求模式有隱藏式、激發式、變動式、目的式四種，且需求模式會隨著尋求的過程而改變。(2)影像內容特徵的比對適合範例式的圖片查詢；傳統文字比對則適合概念式的情景查詢；圖片瀏覽則適合情緒、精神層次的象徵式查詢。(3)與文字檢索不同，在本研究中，表達詳盡的查詢，反而容易造成失敗的影像檢索。(4)影像內容特徵的檢索，適合專業性、單一主題的資料庫，比較不適合用於網路上影像圖片的檢索。

關鍵字

影像內容檢索；資訊尋求行為；使用者研究

並列摘要

The fast increase in digital images has caught increasing attention on the development of image retrieval technologies. Content-based image retrieval (CBIR) has become an important approach in retrieving image data from a large collection. This article reports our results on the use and users study of a CBIR system. Thirty-eight students majored in art and design were invited to use the IBM's QBIC (Query by Image Content) system through the Internet. Data from their information needs, behaviors, and retrieval strategies were collected through an in-depth interview, observation, and self-described think-aloud process. Important conclusions are: (1) There are four types of information needs for image data: implicit, inspirational, everchanging, and purposive. The types of needs may change during the retrieval process. (2) CBIR is suitable for the example-type query, text retrieval is suitable for the scenario-type query, and image browsing is suitable for the symbolic query. (3) Different from text retrieval, detailed description of the query condition may lead to retrieval failure more easily. (4) CBIR is suitable for the domainspecific image collection, not for the images on the Word-Wide Web.

並列關鍵字

Content-based image retrieval ； Information seeking behavior ； Users study

參考文獻

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