Video annotation ‘Prepare-Participate-Connect’ models: Promoting student learning

Active Learning for Video Annotation

In this paper, we present an approach to active learning for video annotation. We use active learning to aide in the semantic labeling of video databases. A software library and simulator have been developed as a tool to investigate and measure the results of active learning. A list of confidence values and nearest neighbor values is maintained for each video segment in the database. A variety ...

Video Annotation in a Learning Environment

Video Corpus Annotation Using Active Learning

Concept indexing in multimedia libraries is very useful for users searching and browsing but it is a very challenging research problem as well. Beyond the systems’ implementations issues, semantic indexing is strongly dependent upon the size and quality of the training examples. In this paper, we describe the collaborative annotation system used to annotate the High Level Features (HLF) in the ...

Learning Rules for Semantic Video Event Annotation

Automatic semantic annotation of video events has received a large attention from the scientific community in the latest years, since event recognition is an important task in many applications. Events can be defined by spatio-temporal relations and properties of objects and entities, that change over time; some events can be described by a set of patterns. In this paper we present a framework ...

Video Annotation and Tracking with Active Learning

We introduce a novel active learning framework for video annotation. By judiciously choosing which frames a user should annotate, we can obtain highly accurate tracks with minimal user effort. We cast this problem as one of active learning, and show that we can obtain excellent performance by querying frames that, if annotated, would produce a large expected change in the estimated object track...