Abstract
The performance of retrieving an image in terms of text-type of queries depends heavily on the quality of the annotated descriptive metadata that describes the content of the images. However, the effective annotation of an image can often be a laborious task that requires consistent domain knowledge. Annotators may annotate features in the images that could not contribute much to retrieval of the images. For effective annotation, an annotation guide agent (AGA) is proposed to aid annotators. Basically AGA monitors the annotator's behaviors and based on the common sense induced from previous annotation instances as well as the domain ontology suggests critical property that will yield the most valuable information for image retrieval. We showed by experiments that the critical property and common sense heuristics used by AGA to aid the annotation of images could significantly lead to the improvement of the recall and precision of image retrieval.
Original language | English |
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Pages (from-to) | 148-161 |
Number of pages | 14 |
Journal | Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) |
Volume | 3371 |
DOIs | |
State | Published - 2005 |
Externally published | Yes |
Event | 7th Pacific Rim International Workshop on Multi-Agents, PRIMA 2004 - Auckland, New Zealand Duration: 08 08 2004 → 13 08 2004 |