Enriching videos with light semantics

This paper describes an ongoing prototypical framework to annotate and retrieve web videos with light semantics. The proposed framework reuses many existing vocabularies along with a video model. The knowledge is captured from three different information spaces (media content, context, document). We also describe ways to extract the semantic content descriptions from the existing usergenerated content using multiple approaches of linguistic processing and Named Entity Recognition, which are later identified with DBpedia resources to establish meanings for the tags. Finally, the implemented prototype is described with multiple search interfaces and retrieval processes. Evaluation on semantic enrichment shows a considerable (50% of videos) improvement in content description

Requirements for an Adaptive Multimedia Presentation System with Contextual Supplemental Support Media

Investigations into the requirements for a practical adaptive multimedia presentation system have led the writers to propose the use of a video segmentation process that provides contextual supplementary updates produced by users. Supplements consisting of tailored segments are dynamically inserted into previously stored material in response to questions from users. A proposal for the use of this technique is presented in the context of personalisation within a Virtual Learning Environment. During the investigation, a brief survey of advanced adaptive approaches revealed that adaptation may be enhanced by use of manually generated metadata, automated or semi-automated use of metadata by stored context dependent ontology hierarchies that describe the semantics of the learning domain. The use of neural networks or fuzzy logic filtering is a technique for future investigation. A prototype demonstrator is under construction

On the automated interpretation and indexing of American football

This work combines natural language understanding and image processing with incremental learning to develop a system that can automatically interpret and index American Football. We have developed a model for representing spatio-temporal characteristics of multiple objects in dynamic scenes in this domain. Our representation combines expert knowledge, domain knowledge, spatial knowledge and temporal knowledge. We also present an incremental learning algorithm to improve the knowledge base as well as to keep previously developed concepts consistent with new data. The advantages of the incremental learning algorithm are that is that it does not split concepts and it generates a compact conceptual hierarchy which does not store instances

TIA1 Mutations in Amyotrophic Lateral Sclerosis and Frontotemporal Dementia Promote Phase Separation and Alter Stress Granule Dynamics.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are age-related neurodegenerative disorders with shared genetic etiologies and overlapping clinical and pathological features. Here we studied a novel ALS/FTD family and identified the P362L mutation in the low-complexity domain (LCD) of T cell-restricted intracellular antigen-1 (TIA1). Subsequent genetic association analyses showed an increased burden of TIA1 LCD mutations in ALS patients compared to controls (p = 8.7 × 1

Content-based Video Retrieval

no abstract

How people find videos

At present very little is known about how people locate and view videos 'in the wild'. This study draws a rich picture of everyday video seeking strategies and video information needs, based on an ethnographic study of New Zealand university students. These insights into the participants' activities and motivations suggest potentially useful facilities for a video digital library