In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
In this paper, the participants of the panel at the 7th ACM SIGMM International Workshop on Multimedia Information Retrieval answer questions about what multimedia is, how MIR is ...
It is estimated that less than ten percent of the world’s species have been discovered and described. The main reason for the slow pace of new species description is that the sc...
A typical way to perform video annotation requires to classify video elements (e.g. events and objects) according to some pre-defined ontology of the video content domain. Ontolo...
We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many conce...
In this paper, we propose a multimodal Web image retrieval technique based on multi-graph enabled active learning. The main goal is to leverage the heterogeneous data on the Web t...
The growing libraries of multimedia objects have increased the need for applications that facilitate search, browsing, discovery, recommendation and playlist construction. Many of...
Robert Ragno, Christopher J. C. Burges, Cormac Her...
In this paper, we propose a novel system, named Video Booklet, which enables efficient and natural personal video browsing and searching. In the system, firstly representative th...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...