In our modern technological world, Computer-Assisted Language learning (CALL) is a new realm towards learning a language in general, and learning L2 vocabulary in particular. It is assumed that the use of multimedia annotations promotes language learners’ vocabulary acquisition. Therefore, this study set out to investigate the effects of different multimedia annotations (still picture annotatio...

Annotation of multimedia resources supports a wide range of applications, ranging from associating metadata with multimedia resources or parts of these resources, to the collaborative use of multimedia resources through the act of distributed authoring and annotation of resources. Most annotation frameworks, however, are based on a closed approach, where the annotations data is limited to the a...

Abstr act. Apart from automated techniques, collaborative multimedia semantic annotation by people, in particular communities of domain experts, are and will be powerful contributors to multimedia semantization. Recently, we extended our LAS server towards an XMPP server, thereby enabling the real time intertwining of communication and the collaborative utilization of remote services, in partic...

This paper presents techniques for multimedia annotation and their application to video summarization and translation. Our tool for annotation allows users to easily create annotation including voice transcripts, video scene descriptions, and visual/auditory object descriptions. The module for voice transcription is capable of multilingual spoken language identification and recognition. A video...

level. The two most important functionalities provided by MPEG-7 are: the decomposition of media assets and the (semantic) annotation of their parts, which we include in our multimedia ontology. Decomposition. MPEG-7 provides descriptors for spatial, temporal, spatio-temporal and media source decompositions of multimedia content into segments. A segment is the most general abstract concept in M...

Active learning is a machine learning technique which chooses the most informative models for labelling and uses them as training data. It has been extensively explored in multimedia research area for reducing human annotation effort. In this article, efforts of active learning in multimedia annotation and retrieval have been surveyed .The application domains such as image or video annotation, ...

Semantic-based storage and retrieval of multimedia data requires accurate annotation of the data. Annotation can be done either manually or automatically. The retrieval performance of the manual annotation based approaches is quite good, as compared to approaches based on automatic annotation. However, manual annotation is time consuming and labor extensive. Therefore, it is quite difficult to ...