Add to ORKGIn this paper we explore a new view on data organisation and retrieval in a (multimedia) collection. We use probabilistic framework for indexing and interactive retrieval of the data, which enable to fill the semantic gap. Semi-automated experiments with TREC-2002 video collection showed that our approach is efficient and effective
This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Exi...
We present a new framework for multimedia content analysis and retrieval which consists of two indep...
Recent content-based video retrieval systems combine output of concept detectors (also known as high...
In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection....
In this paper we propose a new method for data organisation in a (multimedia) collection. We use pro...
The amount of multimedia content increases at a tremendous speed every day -- enabled by ever simple...
This paper proposes a novel scheme for bridging the gap between low level media features and high le...
Our experiments for TRECVID 2004 further investigate the applicability of the so-called “Generative ...
This paper presents a novel Content-Based Video Retrieval approach in order to cope with the semanti...
A probabilistic framework for content-based interactive video retrieval is described. The developed ...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
textabstractWe describe the application of a probabilistic multimedia model to video retrieval. From...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
In this work the problem of content-based information retrieval is approached from a new perspective...
Abstract—Semantic filtering and retrieval of multimedia con-tent is crucial for efficient use of the...
This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Exi...
We present a new framework for multimedia content analysis and retrieval which consists of two indep...
Recent content-based video retrieval systems combine output of concept detectors (also known as high...
In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection....
In this paper we propose a new method for data organisation in a (multimedia) collection. We use pro...
The amount of multimedia content increases at a tremendous speed every day -- enabled by ever simple...
This paper proposes a novel scheme for bridging the gap between low level media features and high le...
Our experiments for TRECVID 2004 further investigate the applicability of the so-called “Generative ...
This paper presents a novel Content-Based Video Retrieval approach in order to cope with the semanti...
A probabilistic framework for content-based interactive video retrieval is described. The developed ...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
textabstractWe describe the application of a probabilistic multimedia model to video retrieval. From...
We present an algorithm for video retrieval that fuses the decisions of multiple retrieval agents in...
In this work the problem of content-based information retrieval is approached from a new perspective...
Abstract—Semantic filtering and retrieval of multimedia con-tent is crucial for efficient use of the...
This paper investigates methods for user and pseudo relevance feedback in video event retrieval. Exi...
We present a new framework for multimedia content analysis and retrieval which consists of two indep...
Recent content-based video retrieval systems combine output of concept detectors (also known as high...