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CVPR
2009
IEEE
1413views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Learning Semantic Scene Models by Object Classification and Trajectory Clustering
The visual surveillance task is to monitor the activity of objects in a scene. In far-field settings (i.e., wide outdoor areas), the majority of visible activities are objects movi...
Hanqing Lu, Stan Z. Li, Tianzhu Zhang
ICIP
2010
IEEE
13 years 5 months ago
A two-pass random forests classification of airborne lidar and image data on urban scenes
Random forests ensemble classifier showed to be suitable for classifying mutlisource data such as lidar and RGB image for urban scene mapping. However, two major problems remain :...
Li Guo, Nesrine Chehata, Samia Boukir
ICPR
2006
IEEE
14 years 8 months ago
Object and Scene Classification: what does a Supervised Approach Provide us?
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...
CVPR
2004
IEEE
14 years 9 months ago
Improving Object Classification in Far-Field Video
Object classification in far-field video sequences is a challenging problem because of low resolution imagery and projective image distortion. Most existing far-field classificati...
Biswajit Bose, W. Eric L. Grimson
SPIEVIP
2010
13 years 10 months ago
Automatic scene activity modeling for improving object classification
In video surveillance, automatic methods for scene understanding and activity modeling can exploit the high redundancy of object trajectories observed over a long period of time. ...
Samuel Foucher, Marc Lalonde, Langis Gagnon