Typical semantic video analysis methods aim for classification of camera shots based on extracted features from a single keyframe only. In this paper, we sketch a video analysis scenario and evaluate ...
Today, semantic concept based video retrieval systems often show insufficient performance for real-life applications. Clearly, a big share of the reason is the lacking performance of the detectors of ...
To solve the problem of indexing collections with diverse text documents, image documents, or documents with both text and images, one needs to develop a model that supports heterogeneous types of doc...
To facilitate finding of relevant information in ever-growing multimedia collections, a number of multimedia information retrieval solutions have been proposed over the past years. The essential eleme...
To exploit the co-occurrence patterns of semantic concepts while keeping the simplicity of context fusion, a novel reranking approach is proposed in this paper. The approach, called ordinal reranking,...
To exploit co-occurrence patterns among features and target semantics while keeping the simplicity of the keyword-based visual search, a novel reranking methods is proposed. The approach, ordinal rera...
To ensure access to growing video collections, annotation is becoming more and more important using background knowledge in the form of ontologies or thesauri is a way to facilitate annotation in a br...
Though both quantity and quality of semantic concept detection in video are continuously improving, it still remains unclear how to exploit these detected concepts as semantic indices in video search,...
This work presents a novel sparse ensemble learning scheme for concept detection in videos. The proposed ensemble first exploits a sparse non-negative matrix factorization (NMF) process to represent d...
This work presents a novel approach to music style recognition inspired by feature extraction techniques used in image classification. To be able to utilize the image classification techniques, the 1D...
This tutorial lays the foundation for the exciting new horizons that arise when multimedia data can automatically be indexed by its semantic content. It will cover basic video analysis techniques, exp...
This study presents an efficient news video querying and browsing system based on distributed news video servers. The proposed architecture includes distributed news video preprocessing (NVP) server a...
This report surveys the state of the art of analysis algorithms and tools for audiovisual content and discusses their feasibility and practical usability, as well as the interdependencies between the ...
This report gives an overview of 3D reconstruction from video sequences. It is to be distributed with the MediaMill3D reconstruction system as an introduction to the theoretical aspects underneath ....
This paper seeks to unravel whether commonly available social tagged images can be exploited as a training resource for concept-based video search. Since social tags are known to be ambiguous, overly ...
This paper provides an overview of the tasks submitted to TRECVID 2011 by ITI-CERTH. ITICERTH participated in the Known-item search (KIS) as well as in the Semantic Indexing (SIN) and the Event Detect...
This paper proposes to improve our previous work on the concept-based video shot indexing, by considering an ontological concept construction in the TRECVid 2007 video retrieval, based on two steps. F...
This paper proposes the use of feature tracks for the detection of concepts in video, particularly dynamic concepts. Feature tracks are defined as sets of local interest points found in different fram...
This paper proposes an elastic spatial verification method for Instance Search, particularly for dealing with non-planar and non-rigid queries exhibiting complex spatial transformations. Different fro...
This paper presents the semantic pathfinder architecture for generic indexing of multimedia archives. The semantic pathfinder extracts semantic concepts from video by exploring different paths through...