Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Ahlberg, Jörgen"'
Autor:
Larsen, Martin Vonheim, Rolfsjord, Sigmund, Gusland, Daniel, Ahlberg, Jörgen, Mathiassen, Kim
The field of visual object tracking is dominated by methods that combine simple tracking algorithms and ad hoc schemes. Probabilistic tracking algorithms, which are leading in other fields, are surprisingly absent from the leaderboards. We found that
Externí odkaz:
http://arxiv.org/abs/2309.12035
Unsupervised learning of anomaly detection in high-dimensional data, such as images, is a challenging problem recently subject to intense research. Through careful modelling of the data distribution of normal samples, it is possible to detect deviant
Externí odkaz:
http://arxiv.org/abs/1905.11034
Ren et al. recently introduced a method for aggregating multiple decision trees into a strong predictor by interpreting a path taken by a sample down each tree as a binary vector and performing linear regression on top of these vectors stacked togeth
Externí odkaz:
http://arxiv.org/abs/1702.08481
Current best local descriptors are learned on a large dataset of matching and non-matching keypoint pairs. However, data of this kind is not always available since detailed keypoint correspondences can be hard to establish. On the other hand, we can
Externí odkaz:
http://arxiv.org/abs/1603.09095
Publikováno v:
In Signal Processing January 2021 178
Binary descriptors of image patches provide processing speed advantages and require less storage than methods that encode the patch appearance with a vector of real numbers. We provide evidence that, despite its simplicity, a stochastic hill climbing
Externí odkaz:
http://arxiv.org/abs/1501.04782
Publikováno v:
Proceedings of the Croatian Compter Vision Workshop, 2014
Localization of salient facial landmark points, such as eye corners or the tip of the nose, is still considered a challenging computer vision problem despite recent efforts. This is especially evident in unconstrained environments, i.e., in the prese
Externí odkaz:
http://arxiv.org/abs/1403.6888
Autor:
Ahlberg, Jörgen
Publikováno v:
Sammanfattning på engelska (spikblad).
Diss. Linköping : Univ., 2002.
Externí odkaz:
http://www.bibl.liu.se/liupubl/disp/disp2002/tek761s.pdf
We describe a method for visual object detection based on an ensemble of optimized decision trees organized in a cascade of rejectors. The trees use pixel intensity comparisons in their internal nodes and this makes them able to process image regions
Externí odkaz:
http://arxiv.org/abs/1305.4537
Autor:
Larsen, Martin Vonheim, Rolfsjord, Sigmund Johannes Ljosvoll, Gusland, Daniel, Ahlberg, Jörgen, Mathiassen, Kim
Publikováno v:
Larsen, Martin Vonheim Rolfsjord, Sigmund Johannes Ljosvoll Gusland, Daniel Ahlberg, Jörgen Mathiassen, Kim . BASE: Probably a Better Approach to Visual Multi-Object Tracking. VISIGRAPP. 2024, 4, 110-121
VISIGRAPP
VISIGRAPP
Externí odkaz:
http://hdl.handle.net/10852/110397