To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Change detection by background subtraction is a common approach to detect moving foreground. The resulting difference image is usually thresholded to obtain objects based on pixel ...
We present a robust road detection and tracking method using multiple vanishing points and the condensation filter. We represent the road using an extended hyperbola model with an...
Particle Filter methods are one of the dominant tracking paradigms due to its ability to handle non-gaussian processes, multimodality and temporal consistency. Traditionally, the e...
Particle filters encode a time-evolving probability density by maintaining a random sample from it. Level sets represent closed curves as zero crossings of functions of two variab...