Registration of Translated and Rotated Images Using Finite Fourier Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the estimation of optical flow: relations between different approaches and some new results
Artificial Intelligence
Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
A model-based 3-D tracking of rigid objects from a sequence of multiple perspective views
Pattern Recognition Letters
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Three dimensional model-based tracking using texture learning and matching
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Non-linear matched filtering for object detection and tracking
Pattern Recognition Letters
Non-linear estimation of image motion and tracking
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
A survey of convergence results on particle filtering methods forpractitioners
IEEE Transactions on Signal Processing
Extension of phase correlation to subpixel registration
IEEE Transactions on Image Processing
Enhanced frequency pattern of the 2-D Hartley transform for a new crop-resilient image transform
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering
Bypass methods for constructing robust automatic human tracking system
Integrated Computer-Aided Engineering
Human automatic detection and tracking for outdoor video
Integrated Computer-Aided Engineering
An efficient GPU implementation of fixed-complexity sphere decoders for MIMO wireless systems
Integrated Computer-Aided Engineering
Scars collaborative telediagnosis platform using adaptive image flow
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering
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This manuscript deals with the problem of 3D object tracking in a multisensor framework. The object is here described by a CAD model. It avoids any image preprocessing that leads, generally, to loss of information. We develop a particle filtering method [6] that we call "correlation-based particle filter" (CBPF) to solve this non-linear estimation problem. The new proposed approach is applied to synthetic and real image sequences of complex 3D moving objects. The originality of this work consists of developing a centralized fusion method that uses, in an optimal way, the measurements delivered by the sensors. In order to optimally using the sensor outcomes, a centralized fusion approach is proposed. The method can jointly estimate 3D pose/motion parameters and track the object in the 3D domain, while many works have been developed in the image plane. Finally, we should mention that the method is not limited in terms of object structure and motion.