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» Dependent Multiple Cue Integration for Robust Tracking
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CVPR
1998
IEEE
15 years 11 months ago
Joint Probabilistic Techniques for Tracking Multi-Part Objects
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...
Christopher Rasmussen, Gregory D. Hager
ICRA
2010
IEEE
135views Robotics» more  ICRA 2010»
14 years 8 months ago
Using multiple hypothesis in model-based tracking
— Classic registration methods for model-based tracking try to align the projected edges of a 3D model with the edges of the image. However, wrong matches at low level can make t...
Céline Teuliere, Éric Marchand, Laur...
BMVC
2001
15 years 12 hour ago
Adaptive Visual System for Tracking Low Resolution Colour Targets
This paper addresses the problem of using appearance and motion models in classifying and tracking objects when detailed information of the object’s appearance is not available....
Pakorn KaewTrakulPong, Richard Bowden
CRV
2009
IEEE
217views Robotics» more  CRV 2009»
15 years 4 months ago
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...
94
Voted
ICIP
2008
IEEE
15 years 11 months ago
Hybrid tracking approach using optical flow and pose estimation
This paper proposes an hybrid approach to estimate the 3D pose of an object. The integration of texture information based on image intensities in a more classical non-linear edge-...
Éric Marchand, Étienne Mémin,...