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» 3D Gait Recognition Using Multiple Cameras
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CVPR
2006
IEEE
15 years 11 months ago
Modeling Correspondences for Multi-Camera Tracking Using Nonlinear Manifold Learning and Target Dynamics
Multi-camera tracking systems often must maintain consistent identity labels of the targets across views to recover 3D trajectories and fully take advantage of the additional info...
Vlad I. Morariu, Octavia I. Camps
CLEAR
2007
Springer
211views Biometrics» more  CLEAR 2007»
15 years 3 months ago
An Appearance-Based Particle Filter for Visual Tracking in Smart Rooms
This paper presents a visual particle filter for tracking a variable number of humans interacting in indoor environments, using multiple cameras. It is built upon a 3-dimensional,...
Oswald Lanz, Paul Chippendale, Roberto Brunelli
MM
2005
ACM
188views Multimedia» more  MM 2005»
15 years 3 months ago
Detecting group activities using rigidity of formation
Most work in human activity recognition is limited to relatively simple behaviors like sitting down, standing up or other dramatic posture changes. Very little has been achieved i...
Saad M. Khan, Mubarak Shah
FGR
2006
IEEE
194views Biometrics» more  FGR 2006»
15 years 3 months ago
Robust Multi-View Multi-Camera Face Detection inside Smart Rooms Using Spatio-Temporal Dynamic Programming
Robust face detection presents a difficult problem in real interaction scenarios, that, in order to achieve, most often requires employing additional sources of information. In t...
ZhenQiu Zhang, Gerasimos Potamianos, Ming Liu, Tho...
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...