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» 3D Motion Reconstruction for Real-World Camera Motion
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SENSYS
2006
ACM
14 years 2 months ago
Virtual high-resolution for sensor networks
The resolution at which a sensor network collects data is a crucial parameter of performance since it governs the range of applications that are feasible to be developed using tha...
Aman Kansal, William J. Kaiser, Gregory J. Pottie,...
CGF
2008
201views more  CGF 2008»
13 years 8 months ago
Fluid in Video: Augmenting Real Video with Simulated Fluids
We present a technique for coupling simulated fluid phenomena that interact with real dynamic scenes captured as a binocular video sequence. We first process the binocular video s...
Vivek Kwatra, Philippos Mordohai, Rahul Narain, Sa...
CRV
2004
IEEE
160views Robotics» more  CRV 2004»
14 years 13 days ago
A New Integrative Approach to Time Varying Image Interpretation
- This paper presents a global method to process monocular image sequences for mobile robot obstacle detection. We do not aim to achieve a complete scene reconstruction, but only t...
Philippe Guermeur
NIPS
2004
13 years 10 months ago
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...
IROS
2007
IEEE
154views Robotics» more  IROS 2007»
14 years 3 months ago
A Kalman filter-based algorithm for IMU-camera calibration
—Vision-aided inertial navigation systems (V-INSs) can provide precise state estimates for the 3-D motion of a vehicle when no external references (e.g., GPS) are available. This...
Faraz M. Mirzaei, Stergios I. Roumeliotis