the Kernel Particle Filter (KPF)—is proposed for visual tracking in image sequences. The KPF invokes kernels to form a continuous estimate of the posterior density function. Particles are allocated based on the gradient information estimated

Particle filters are often used for tracking objects within a scene. As the prediction model of a particle filter is often implemented using basic movement predictions such as ran- domwalk,constantvelocityoracceleration,thesemodelswill us

This paper introduces a new object tracking method which combines two algorithms working in parallel, and based on low-level observations (colour and gradient orientation): the Generalised Hough Transform, using a pixel-based descr iption, and