A Survey on Interactive Video Retrieval Using Active Learning Approach

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, Relevance feedback and contentbased image retrieval are mainly focussed. The principle of active learning has been briefly discussed and then sample selection criteria were analyzed. Classification models used in active learning-based multimedia annotation and retrieval, including semi-supervised learning, Support vector machine has been discussed. In particular, large-scale interactive multimedia annotation and analysis of human annotation with several strategies were briefly discussed.