Author of the book 'Scale-Space Theory in Computer Vision'. Has numerous publications on scale-space theory with applications, which can be found on Google Scholar or ResearchGate.
Research Experience
Works at the Division of Computational Science and Technology, KTH Royal Institute of Technology. Research areas include scale-space theory and its applications, image-based matching and recognition, normative theory for auditory receptive fields, scale-space theory for visual operations, and time-causal and time-recursive receptive fields.
Background
Professor of Computer Science—Computational Vision. Main research areas include scale-space theory, early vision and image representations, particularly in terms of receptive fields for visual tasks such as feature detection, image matching, object recognition, spatio-temporal recognition, and video analysis, as well as computational modeling of biological vision. He also works on computational modeling of hearing and has previously worked on topics in medical image analysis, brain activation, and gesture recognition.
Miscellany
Interests also include computational modeling of hearing and medical image analysis.