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Content-Based Image Retrieval at the End of the Early Years
The working conditions of content-based retrieval: patterns of use, types of pictures, the role of semantics, and the sensory gap are discussed, as well as aspects of system engineering: databases, system architecture, and evaluation. Expand
The challenge problem for automated detection of 101 semantic concepts in multimedia
We introduce the challenge problem for generic video indexing to gain insight in intermediate steps that affect performance of multimedia analysis methods, while at the same time fosteringExpand
Learning Social Tag Relevance by Neighbor Voting
This paper proposes a neighbor voting algorithm which accurately and efficiently learns tag relevance by accumulating votes from visual neighbors and proves that the algorithm is a good tag relevance measurement for both image ranking and tag ranking. Expand
Early versus late fusion in semantic video analysis
It is shown by experiment on 184 hours of broadcast video data and for 20 semantic concepts, that late fusion tends to give slightly better performance for most concepts, however, for those concepts where early fusion performs better the difference is more significant. Expand
ICDAR 2003 robust reading competitions: entries, results, and future directions
This paper broke down the robust reading problem into three subproblems and run competitions for each stage, and also a competition for the best overall system, and described an algorithm for combining the outputs of the individual text locators and showed how the combination scheme improves on any of theindividual systems. Expand
Multimodal Video Indexing: A Review of the State-of-the-art
A unifying and multimodal framework is put forward, which views a video document from the perspective of its author, which forms the guiding principle for identifying index types, for which automatic methods are found in literature. Expand
Concept-Based Video Retrieval
This paper presents a component-wise decomposition of such an interdisciplinary multimedia system, covering influences from information retrieval, computer vision, machine learning, and human–computer interaction and lays down the anatomy of a concept-based video search engine. Expand
Classification of user image descriptions
A framework for the classification of image descriptions by users is developed, based on various classification methods from the literature, which suggests that users prefer general descriptions as opposed to specific or abstract descriptions. Expand
Adding Semantics to Detectors for Video Retrieval
An automatic video retrieval method based on high-level concept detectors, i.e., a set of machine learned concept detectors that is enriched with semantic descriptions and semantic structure obtained from WordNet, and their combined potential using oracle fusion is discussed. Expand
Learning tag relevance by neighbor voting for social image retrieval
A novel algorithm that scalably and reliably learns tag relevance by accumulating votes from visually similar neighbors is proposed, and treated as tag frequency, learned tag relevance is seamlessly embedded into current tag-based social image retrieval paradigms. Expand