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Projects / Programmes source: ARIS

Computer Vision

Periods
Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   

Code Science Field
P170  Natural sciences and mathematics  Computer science, numerical analysis, systems, control 
P176  Natural sciences and mathematics  Artificial intelligence 
T111  Technological sciences  Imaging, image processing 
T125  Technological sciences  Automation, robotics, control engineering 
Evaluation (rules)
source: COBISS
Researchers (9)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  11161  PhD Aleš Jaklič  Computer science and informatics  Researcher  2001 - 2003  119 
2.  20332  PhD Matjaž Jogan  Computer science and informatics  Researcher  2001 - 2003  45 
3.  15621  PhD Bojan Kverh  Computer science and informatics  Researcher  2001 - 2003  34 
4.  05896  PhD Aleš Leonardis  Computer science and informatics  Researcher  2001 - 2003  455 
5.  19224  MSc Igor Lesjak  Computer science and informatics  Researcher  2001 - 2003  16 
6.  06618  PhD Jasna Maver  Computer science and informatics  Researcher  2001 - 2003  99 
7.  19226  PhD Peter Peer  Computer science and informatics  Researcher  2001 - 2003  394 
8.  18198  PhD Danijel Skočaj  Computer science and informatics  Researcher  2001 - 2003  306 
9.  09581  PhD Franc Solina  Computer science and informatics  Head  2001 - 2003  638 
Organisations (1)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  1539  University of Ljubljana, Faculty of Computer and Information Science  Ljubljana  1627023  16,011 
Abstract
Our research interests cover all aspects of computer vision. Computer vision generally interprets images which represent a 3D environment. Images can be captured with optical systems (i.e. video camera) or special sensors such as range sensors or medical imaging systems which capture the internal structure of 3D bodies (i.e. CAT, NMR). The results of interpretation depend on the goal or the role of computer vision in the overall system (i.e. identification of a person on a photography or visual navigation of a mobile robot). The interpretation results can be the segmentation of an image into semantic units, a geometric description of the scene, object tracking parameters, identification of classification of objects on the image etc. The main reasons why 3D interpretation of images is difficult are: - when a 3D scene is projected on a 2D image plane, - segmentation of an image into meaningful parts depends on the recognition of those parts, - understanding of human and biological vision is also not complete Goals of our research program are: - identification of models and algorithms which are beside the image information crucial for image interpretation - development of computer vision systems for solving specific problems (i.e. reconstruction of CAD models from images, content-based search of image databases, object recognition).
Most important scientific results Final report
Most important socioeconomically and culturally relevant results Final report
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