Multimedia Computing Group

The Multimedia Computing (MMC) Group develops algorithms for enriching, accessing, and searching large quantities of data. Such algorithms lie at the core of tomorrows’ search engines and large-scale recommender systems. The group sets its focus on developing systems that are oriented to the needs of users, and that solve the challenges faced by large-scale online content and service providers. Multimedia data analytics also has applications in the full range of fields that benefit from data science, including health, telecom, and geosciences.

The group has a track record of developing technologies that make possible optimized interaction with large collections of multimedia data (e.g., images, video, and music) in real-world contexts (e.g., within social networks). Our work requires a combination of mathematical models, machine learning techniques, and practical skills in algorithm development and evaluation. The members of the MMC group share expertise in multimedia information retrieval, recommender systems, multimedia signal processing, social network analysis, human computation (crowdsourcing) and quality of experience. Collaborations include joint work with researchers from Yahoo Labs, Telefónica Research, Microsoft Research and Google.

     

The work being carried out in the MMC Group encompasses a broad palette of research directions including:

  • Multimedia content analysis and search
    • Semantics extraction from multimedia data
    • Multi-modal query expansion
    • Multi-source search result reranking
  • Multimedia information retrieval in a social network context
    • Modeling information propagation and relationships in social networks
    • Collaborative recommender systems
    • Social recommendation
  • Interaction with multimedia content
    • (Affective) User profiling
    • User (search/uploader) intent
    • Query failure prediction
    • Quality of multimedia experience
  • Multimedia content management
    • Multimedia databases and dataspaces
    • Entity retrieval

More information about the research directions and activities of the MMC Group can be found under research projects or on the sites of group members.

     

News

18 juli 2019

Huijuan Wang, Co-founder and Chair of Dutch Network Science Society, Board member of the international Network Science Society

Huijuan Wang and Linda Douw (Amsterdam UMC) have founded the Dutch Network Science Society http://www.netsci.nl, which kicked off with a national symposium http://www.netsci.nl/node/4 on 7th May 2019 at TUDelft. Dutch Network Science Society is the Dutch Chapter of the international Network Science Society https://netscisociety.net/

18 juli 2019

Huijuan Wang is on the Editorial Board of Nature’s Scientific Report.

More about the journal Scientific Report by Nature can be found here https://www.nature.com/srep/

30 juni 2019

Odette Scharenborg on Dutch national television in Nieuwsuur

Recently, TU Eindhoven presented their plans to open their positions for scientific staff temporarily only for women. Odette Scharenborg reacted on Dutch national television in Nieuwsuur (at 26.40) on the plans of TU/e.

12 mei 2019

Odette Scharenborg Associate Editor

Odette Scharenborg has been appointed as an Associate Editor of the IEEE journal Signal Processing Letters. The IEEE journal Signal Processing Letters is one of the flagship journals of the IEEE Signal Processing Society

12 mei 2019

The Multimedia Computing Group cordially invites you to a Music Information Retrieval morning seminar, Wednesday, May 15, Social Data Lab.

The Artificial Intelligence Lab at the Otto von Guericke University Magdeburg is dedicated to improving the cognitive abilities of machines and reducing the friction in human-machine interaction. We investigate novel signal processing and deep learning algorithms for the analysis of sensory data and investigate human-centric approaches to interacting with machines such as speech, EEG or eye tracking. This opens up richer communication channels to remedy the interface bottleneck between human and machine and introduces feedback mechanisms that make communication more robust.