We propose a multi-wing harmonium model for mining multimedia data that extends and improves on earlier models based on two-layer random fields, which capture bidirectional dependencies between hidden...
We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a ...
Video retrieval is one of the most famous issues in multimedia research. Users express their needs in terms of queries and expect to retrieve most relevant answers. This task is becoming harder due to...
Video retrieval compares multimedia queries to a video collection in multiple dimensions and combines all the retrieval scores into a final ranking. Although text are the most reliable feature for vid...
Typical approaches to the multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computational bottleneck f...
This paper provides an overview of a pilot evaluation of video summaries using rushes from several BBC dramatic series. It was carried out under the auspices of TRECVID. Twenty-two research teams subm...
This paper describes an evaluation of automatic video summarization systems run on rushes from several BBC dramatic series. It was carried out under the auspices of the TREC Video Retrieval Evaluation...
This document describes a system designed to perform automatic production of semantic labels on media content, for the purposes of content classification, browse and retrieval. Specialised classifiers...
The thesis discusses and evaluates a model of video information retrieval that incorporates a variation of Relevance Feedback and facilitates object-based interaction and ranking. Object-based feature...
The personalized Electronic Program Guide (pEPG) has been touted as a possible solution to the information overload problem faced by Digital TV (DTV) users. It leverages artificial intelligence and us...
The explosion of multimedia content in databases, broadcasts, streaming media, etc. has generated new requirements for more effective access to these global information repositories. Content extractio...
The emerging popularity of multimedia data, as digital representation of text, image, video and countless other milieus, with prodigious volumes and wild diversity, exhibits the phenomenal impact of m...
The effectiveness of a video retrieval system largely depends on the choice of underlying text and image retrieval components. The unique properties of video collections (e.g., multiple sources, noisy...
The acoustic environment provides a rich source of information on the types of activity, communication modes, and people involved in many situations. It can be accurately classified using recordings f...
Temporal consistency is ubiquitous in video data, where temporally adjacent video shots usually share similar visual and semantic content.This paper presents a thorough study of temporal consistency d...
Recent years have witnessed an increased interest in transfer learning. Despite the vast amount of research performed in this field, there are remaining challenges in applying the knowledge learnt fro...
Ranking large scale image and video collections usually expects higher accuracy on top ranked data, while tolerates lower accuracy on bottom ranked ones. In view of this, we propose a rank learning al...
Ranking large scale image and video collections usually expects higher accuracy on top ranked data, while tolerates lower accuracy on bottom ranked ones. In view of this, we propose a rank learning al...
Novelty detection is defined as the detection of documents that provide "new" or previously unseen information. "New information" in a search result list is defined as the incremental information foun...
Multi-modal data is dramatically increasing with the fast growth of social media. Learning a good distance measure for data with multiple modalities is of vital importance for many applications, inclu...