A. Pizurica: research interests

Artificial Intelligence in Machine Vision

I am interested in understanding and modeling computational mechanisms behind the human visual system, and employing these to advance intelligent machine vision algorithms. Some components of this research are

• Graphical models and inference

• Sparse coding and dictionary learning

• Supervised and unsupervised classification

• Object and scene descriptors

• (Moving) object detection and tracking

Selected related publications

• W. Liao, M. Dalla Mura, J. Chanussot and A. Pižurica, "Fusion of spectral and spatial information for classification of hyperspectral remote-sensed imagery by local graph," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 2, pp. 583-594, 2016.

• A. Frías-Velázquez, P. Van Hese, A. Pižurica and W. Philips, "Split-and-Match: A Bayesian Framework for Vehicle Re-identification in Road Tunnels", Engineering Applications of Artificial Intelligence, vol. 45, pp. 220-233, 2015.

• T. Ružic and A. Pižurica, “Context-aware patch-based image inpainting using Markov random field modeling,” IEEE Transactions on Image Processing, vol. 24, no. 1, pp. 444-456, Jan 2015.

• A. Latic and A. Pizurica, “Dictionary learning techniques for painter style identification: case study on the Ghent Altarpiece”, IEICE International Conference Information and Communication Technology Forum ICTF, 2014, May 28-30, Poznan, Poland

• A. Pižurica, L. Platisa, T. Ružic, B. Cornelis, A. Dooms, M. Martens, H. Dubois, B. Devolder, M. De Mey and I. Daubechies, “Digital Image Processing of the Ghent Altarpiece: Supporting the painting's study and conservation treatment", IEEE Signal Processing Magazine, vol. 32, no. 4, pp. 112-122, July 2015.

• V. Jelaca, A. Pižurica, J. Niño Castañeda, A. Frias Velazquez and W. Philips, "Vehicle matching in smart camera networks using image projection profiles at multiple instances", Image and Vision Computing, vol. 31, no. 9, pp. 673-685, 2013.

• S. Grünwedel, N. Petrovic, LJ. Jovanov, J. Niño Castañeda, A. Pižurica and W. Philips, "Efficient foreground detection for real-time surveillance applications", Electronics Letters, vol. 49, no. 18, pp. 1143-1144, 2013.

• W. Liao, A. Pižurica, W. Philips and Y. Pi, “Semisupervised Local Discriminant Analysis for Feature Extraction in Hyperspectral Images”, IEEE Transactions on Geoscience and Remote Sensing, vol. 51 no. 1, pp. 184 – 198, Jan 2013.

• T. Ružic, A. Pižurica and W. Philips, “Neighbourhood-consensus message passing as a framework for generalized iterated conditional expectations,” Pattern Recognition Letters, Vol. 33, No. 3, pp. 309-318, Feb 2012.