Object counting is crucial in applications ranging from cell growth analysis, to crowd estimation in video surveillance systems, to product counting on production lines. Classical methods are not applicable in these cases because they require large annotated training sets and struggle in dense scenarios. On the other hand, the methods developed at the Visual Cognitive Systems Laboratory at the Faculty of Computer Science and Information Science, University of Ljubljana, develop accurate counting with just a few training examples and represent a methodological leap in computer vision.
