Research groups of the UB

Barcelona Perceptual Computing Laboratory (BCNPCL)


Principal researchers: Petia Radeva i Dr. Jordi Vitrià.

Members: Dr. Simone Balocco, Dra. Laura Igual, Dr. Santi Seguí, Michal Drozdzal, Ekaterina Zaytseva, Maedeh Aghaei, Marc Bolaños.

Facilities and equipment

Current techniques of computer vision often require a lot of calculations on a large number of images. The group has at its disposal a large cluster of more than 500 processing cores of Applied Mathematics Department into Mathematics Faculty UB enables tackling big projects of computer vision. The group also maintains a close relationship with the Computer Vision Center ( ) which allows you to share specific resources in this area.


University of Barcelona. Department of Applied Mathematics and Analysis, Faculty of Mathematics. Gran Via de les Corts Catalanes, 585, 08007 Barcelona.


The Barcelona Perceptual Computing Laboratory (BCNPCL) of the University of Barcelona works in two main areas:

  • Object recognition. Developing and applying new techniques in various sectors to detect and track people, and for the automatic classification of different types of objects (food items, cars, traffic signals, etc.)
  • Medical image analysis. Extensive experience in the processing and analysis of three highly innovative medical procedures:
  1. Intravascular ultrasound images applied to analyze coronary diseases
  2. Intraluminal images applied to the detection of intestinal motility disorders;
  3. Images of the brain applied to diagnose various mental diseases (hyperactivity, obesity, etc.)

The group is part of the Department of Applied Mathematics Department of the Faculty of Mathematics at the University of Barcelona.



The group is open to provide services in the following areas:

Applications of the techniques of detection and analysis of people. Detection of people to count the number of people that pass through a given point of a store or for a customer classification demographic (age, gender, race).

The object recognition applied in different productive sectors.  Automatic detection of cars and people to develop support systems driving.

Mobile applications and new web technologies to apply computer vision analysis to scenarios where human interaction is needed.



The group has done projects for companies such as: La Caixa, Boston Sci, Given Imaging, Lilly, Institut Cartogràfic de Catalunya, etc.

Industry Sectors

Computer vision is a horizontal technology that has found applications in virtually all economic sectors:

  • Commercial Sector: chain stores, supermarkets, cooperatives, etc.
  • Industrial sector: food, electronics, textiles, etc.
  • Health sector: medical research, healthy lifestyle, technology, diagnostics, etc.
  • TIC Sector: sensing, web systems, mobile, embedded systems, etc.
  • Sector multimedia and video games: an analysis of human behaviour, etc.


Currently the two most active areas of research are related to the following topics:

  • Recognition of food images.
  • Image analysis of portable cameras for applications related to the lifestyle of the people or their memory.


Transfer Activities

Among the latter group collaborations can include:

  • The development of a system for automatic detection of polypsin imagesin traluminal injection for the company Given Imaging(Israel).
  • Developing a system for as sessing intestinal motility from imagesin traluminal injection for the company Given Imaging(Israel).
  • The development of a system forseg mentation of the coronary plaque using intra vascular images for the company Boston Sci(USA).
  • The development of a system of inspection of corks for the company Inspecta SL.


  • Borjas, J.Vitria, P.Radeva. Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments. 13th IAPR Conf. on Machine Vision Applications, Japan, 2013.
  • Bolaños M., Garolera M.; Radeva P.; Active Labeling Application Applied to Food-Related Object Recognition, 5th Worksh. Multimedia for Cooking and Eating Activities, ACM ICME2013, Barcelona.
  • Segui, S.; Drozdzal, M.; Vilarino, F.; Malagelada, C.; Azpiroz, F.; Radeva, P.; Vitria, J.; Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy, Information Technology in Biomedicine, IEEE Transactions on , vol.16, no.6, pp.1341-1352, Nov. 2012.
  • Alberti, M.; et al. “Automatic Non-Rigid Temporal Alignment of Intravascular Ultrasound Sequences: Method and Quantitative Validation” Ultrasound in medicine & biology 39.9 (2013): 1698-1712.
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