Montse Pardàs


Montse Pardàs received the MS degree in telecommunications and the Ph. D. degree from the Polytechnic University of Catalonia, Barcelona, Spain, in July 1991 and January 1995, respectively. From September 1994 she has been teaching under-graduate and graduate courses in the area of communication systems, digital image processing and computer vision in this University, where she is currently Professor. From January 1999 to December 1999 she was a research visitor at Bell Labs, Lucent Technologies, in New Jersey, and from July 2019 to June 2020 at Toshiba’s Cambridge Research Lab (Computer Vision group). Her main research interests include image and video analysis using mathematical morphology and deep learning, with a special emphasis on segmentation and object tracking applications. 

She has served as associate editor of journals such as EURASIP Journal on Advances in Signal Processing and ISRN Machine Vision, as technical co-chair for the international conference EUSIPCO 2011 and as regular reviewer for image processing and computer vision conferences.


Book Chapters and Bookstop

J. Gallego, Pardàs, M., and Solano, M., Foreground objects segmentation for moving camera scenarios based on SCGMM, in Computational Intelligence for Multimedia Understanding, vol. 7252, Berlin Heidelberg: Springer, 2012, pp. 195-206.
M. Alcoverro, Casas, J., and Pardàs, M., Skeleton and shape adjustment and tracking in multicamera environments, in Lecture notes in computer science, vol. 6169/2010, Berlin / Heidelberg: Springer, 2010, pp. 88–97.
C. Canton-Ferrer, Pardàs, M., and Vilaplana, V., Image and video processing tools for HCI, in Multimodal signal processing: theory and applications for human-computer interaction, 2009, pp. 93–118.
K. Nickel, Pardàs, M., Stiefelhagen, R., Canton-Ferrer, C., Landabaso, J. - L., and Casas, J., Activity Classification, in Computers in the Human Interaction Loop, London: Springer, 2009, pp. 107–119.
C. Canton-Ferrer, Casas, J., and Pardàs, M., Head Orientation Estimation Using Particle Filtering in Multiview Scenarios, in Multimodal Technologies for Perception of Humans, vol. 4625, Berlin / Heidelberg: Springer, 2008, pp. 317–327.

Conference Papers top

M. Pardàs and Canet, G., Refinement network for unsupervised on the scene foreground segmentation, in EUSIPCO European Signal Processing Conference, 2020.
X. Lin, Casas, J., and Pardàs, M., One Shot Learning for Generic Instance Segmentation in RGBD Videos, in International Conference on Computer Vision, Theory and Applications, Prague, 2019. (1.64 MB)
D. Sanchez-Escobedo, Lin, X., Casas, J., and Pardàs, M., HybridNet for Depth Estimation and Semantic Segmentation, in ICASSP 2018, Calgary, Alberta, Canada, 2018. (1.14 MB)
X. Lin, Casas, J., and Pardàs, M., 3D Point Cloud Segmentation Using a Fully Connected Conditional Random Field, in The 25th European Signal Processing Conference (EUSIPCO 2017), Kos island, Greece, 2017. (2.34 MB)
X. Lin, Casas, J., and Pardàs, M., Graph based Dynamic Segmentation of Generic Objects in 3D, in CVPR SUNw: Scene Understanding Workshop, Las Vegas, US, 2016. (956.15 KB)