Peter Lambert

Peter Lambert

Peter Lambert

email: Peter.Lambert@UGent.be
tel.: +32 9 331 49 93
research group: IDLab
team website

Peter Lambert is a full-time Associate Professor at the Internet Technology and Data Science Lab (IDLab) of Ghent University – imec (Belgium) since 2013, where he coordinates the research team “MEDIA”. He received his Master’s degree in science (mathematics) and in applied informatics from Ghent University in 2001 and 2002, respectively, and he obtained the Ph.D. degree in computer science in 2007 at the same university. Between 2010 and 2013, he was a Technology Developer at Ghent University. His research interests include multimedia signal processing, visual communication, computer graphics, and AR/VR.

Keywords: augmented & virtual reality (AR/VR), multimedia signal processing, visual communication, computer graphics

Key publications

  • Verhack, R., Van Wallendael, G., Courteaux, M., Lambert, P., & Sikora, T. (2018). Progressive Modeling of Steered Mixture-of-Experts for Light Field Video Approximation. 2018 Picture Coding Symposium (PCS) (pp. 268–272). Presented at the PCS2018, the Picture Coding Symposium , IEEE.

  • De Praeter, J., Van Wallendael, G., Slowack, J., & Lambert, P. (2017). Video encoder architecture for low-delay live-streaming events. IEEE TRANSACTIONS ON MULTIMEDIA, 19(10), 2252–2266.

  • De Praeter, J., Duchi, P., Van Wallendael, G., Macq, J.-F., & Lambert, P. (2016). Efficient encoding of interactive personalized views extracted from immersive video content. 1st International Workshop on Multimedia Alternate Realities (pp. 25–30). Presented at the 1st International Workshop on Multimedia Alternate Realities (AltMM 2016), New York, NY, USA: ACM.

  • Pham Van, L., De Cock, J., Van Wallendael, G., Van Leuven, S., Rodriguez-Snchez, R., Martnez, J., Lambert, P., et al. (2013). Fast transrating for high efficiency video coding based on machine learning. IEEE International Conference on Image Processing ICIP (pp. 1573–1577). Presented at the 20th IEEE International Conference on Image Processing (ICIP), IEEE.

  • Bailleul, R., De Cock, J., Schrauwen, B., Lambert, P., & Van de Walle, R. (2013). Content feature based bit rate modelling for scalable video coding using machine learning algorithms. IEEE International Conference on Multimedia and Expo Workshops. Presented at the IEEE International conference on Multimedia and Expo Workshops (ICMEW 2013), New York, NY, USA: IEEE.

Publication links