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ICCV
2007
IEEE
14 years 9 months ago
Learning to Find Object Boundaries Using Motion Cues
While great strides have been made in detecting and localizing specific objects in natural images, the bottom-up segmentation of unknown, generic objects remains a difficult chall...
Andrew N. Stein, Derek Hoiem, Martial Hebert
ECCV
2008
Springer
14 years 9 months ago
Learning Spatial Context: Using Stuff to Find Things
The sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the...
Geremy Heitz, Daphne Koller
ISMIS
2005
Springer
14 years 27 days ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
ICCV
2005
IEEE
14 years 1 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
ICIP
2007
IEEE
14 years 9 months ago
Rotation Detection using the Curl Equation
Rotational types of motion can often be seen in video sequences. However, not a lot of research has been done to investigate rotational motion models for use in video. Analysing t...
Daire Lennon, Naomi Harte, Anil C. Kokaram