Combining heterogeneous sources in an interactive multimedia content retrieval model

Combining Concept-with Content-Based Multimedia Retrieval

Interactive Indexing and Retrieval of Multimedia Content

The indexing and retrieval of multimedia items is difficult due to the semantic gap between the user’s perception of the data and the descriptions we can derive automatically from the data using computer vision, speech recognition, and natural language processing. In this contribution we consider the nature of the semantic gap in more detail and show examples of methods that help in limiting th...

Probabilistic Models for Combining Diverse Knowledge Sources in Multimedia Retrieval

In recent years, the multimedia retrieval community is gradually shifting its emphasis from analyzing one media source at a time to exploring the opportunities of combining diverse knowledge sources from correlated media types and context. In order to combine multimedia knowledge sources, two basic issues must be addressed: what to combine and how to combine. While considerable effort has been ...

Nonlinear combining of heterogeneous features in content-based image retrieval*

In content-based image retrieval (CBIR), retrieval based on different features can be various by the way how to combine the feature values. Most of the existing approaches assume a linear relationship between different features, and the usefulness of such systems was limited due to the difficulty in representing high-level concepts using low-level features. In this paper, we introduce Neural Ne...

Content-based Multimedia Data Retrieval on Heterogeneous System Environment

In this paper, we propose a static data partitioning scheme for content-based multimedia data retrieval using a heterogeneous cluster system. Multimedia data is represented by unified k-tree structure of kdimensional(k-d) signals proposed in [6]. Each dimension of k-d data is separated into small blocks and then formed into a hierarchical multidimensional tree structure, called a k-tree. The pa...