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CVPR
1999
IEEE
15 years 24 days ago
Object Recognition with Color Cooccurrence Histograms
We use the color cooccurrence histogram (CH) for recognizing objects in images. The color CH keeps track of the number of pairs of certain colored pixels that occur at certain sep...
Peng Chang, John Krumm
IJCV
2008
188views more  IJCV 2008»
13 years 10 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
JVCA
2006
110views more  JVCA 2006»
13 years 10 months ago
As-consistent-As-possible compositing of virtual objects and video sequences
We present an efficient approach that merges the virtual objects into video sequences taken by a freely moving camera in a realistic manner. The composition is visually and geomet...
Guofeng Zhang, Xueying Qin, Xiaobo An, Wei Chen, H...
ICRA
2006
IEEE
139views Robotics» more  ICRA 2006»
14 years 4 months ago
Tracking Unobservable Rotations by Cue Integration
— Model based object tracking has earned significant importance in areas such as augmented reality, surveillance, visual servoing, robotic object manipulation and grasping. Alth...
Ville Kyrki, Danica Kragic
ICCV
2009
IEEE
1068views Computer Vision» more  ICCV 2009»
15 years 3 months ago
Illumination Aware MCMC Particle Filter for Long-Term Outdoor Multi-Object Simultaneous Tracking and Classification
This paper addresses real-time automatic visual tracking, labeling and classification of a variable number of objects such as pedestrians or/and vehicles, under timevarying illu...
Franc¸ois Bardet, Thierry Chateau, Datta Ramadasa...