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This paper describes a particle filter based approach for estimating the ground plane from an image sequence. Based on a Bayesian framework, the particle filter provides a robust estimation of the plane parameters, since it can handle non-linearities, while allowing a high flexibility for integrating new cues into the system. Furthermore, the different modes of the resulting probability density function...
Road region is an important information for guidance of autonomous vehicles or robots. The goal of this research is to develop robust monocular algorithm suitable for region based road detection. This paper deals with a problem, how to estimate probability density function (pdf) of road region appearing in sequential images. The key idea is to construct pdf from temporal sequence of observations throughout...
We present a new approach to the general problem of template-based detection, segmentation, and registration of elastically deformable objects. This joint problem is highly nonlinear and high dimensional, due to the large space of possible geometric transformations between a given template and its observed signature. Hence, any attempt to directly solve it inevitably leads to a high dimensional, nonlinear,...
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