Paper
Knowledge-Based Semantic Retrieval of Multimedia and Image Objects Using Collaborative Indexing
- Authors:
- Prof. C. H. C. Leung; Yuanxi Li; W. S. Chan
- Abstract
- With the rapid development of multimedia technology, digital resources has become increasingly available and it constitutes a significant component of multimedia contents on the Internet. Since digital resources can be represented in various forms, formats, and dimensions, searching such information is far more challenging than text-based search. While some basic forms of multimedia retrieval are available on the Internet, these tend to be inflexible and have significant limitations. Currently, most of these multimedia retrieval systems mainly rely on text annotations. Here, we present an approach for deep concept-based multimedia information retrieval, which focuses on high-level human knowledge, perception, incorporating subtle nuances and emotional impression on the multimedia resources. We also provide a critical evaluation of the most common current Multimedia Information Retrieval approaches and propose an innovative adaptive method for multimedia information search that overcomes the current limitations. The main focus of our approach is concerned with image discovery and recovery by collaborative semantic indexing and user relevance feedback analysis. Through successive usage of our indexing model, novel image content indexing can be built from deep user knowledge incrementally and collectively by accumulating users’ judgment and intelligence.
- Keywords
- Collaborative Indexing; Multimedia Indexing; Image Information Retrieval; Relevance Feedback; Semantic Search
- StartPage
- 179
- EndPage
- 187
- Doi