Active vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
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In this paper, we present a novel approach for pose estimation and tracking of license plates from monocular camera view. Given an initial estimate, we try to track the location, motion vector and pose of the object in 3D in the successive video frames. We utilize Condensation algorithm for estimating the state of the object and filtering the measurements, according to the extracted image features. We utilize directional gradients as the image features. Each sample of the Condensation algorithm is projected to the image plane by perspective camera model. The overlapping of the image gradients and the sample boundaries, gives a likelihood for each sample of the Condensation algorithm. Our contribution is utilizing condensation algorithm for rigid object tracking, where the object is tracked in 3D. We demonstrate the performance of the approach by tracking license plates in outdoor environment with different motion trajectories.