1. A method of tracking objects in a series of n-D images that have objects appearing in a background comprising using a probabilistic model of the appearance of the objects and of the appearance of the background in the images, and using an evaluation of whether particular pixels in the images are a part of an object or a part of the background, that evaluation comprising determining the posterior model probabilities that a particular pixel or group of pixels belongs to an object or to the background, and further comprising marginalising over these object/background membership probabilities to yield a function of the pose parameters of the objects, where at least the object/background membership is adjudged to be a nuisance parameter and marginalised out; wherein a processor is configured to perform an evaluation of equation (3) followed by an evaluation of equation (4), wherein: ⁢ P ⁡ ( M j ❘ y ) = P ⁡ ( y ❘ M j ) ⁢ P ⁡ ( M j ) ∑ { i = f , b } ⁢ P ⁡ ( y ❘ M i ) ⁢ P ⁡ ( M i ) ⁢ ⁢ j = { f , b } Equation ⁢ ⁢ ( 3 ) ⁢ ⁢ is P ⁡ ( Φ , p ❘ x , y ) = 1 P ⁡ ( x ) ⁢ ∑ { i = f , b } ⁢ { P ⁡ ( x ❘ Φ , p , M i ) ⁢ P ⁡ ( M i ❘ y ) } ⁢ P ⁡ ( Φ ) ⁢ P ⁡ ( p ) and ⁢ ⁢ Equation ⁢ ⁢ ( 4 ) ⁢ ⁢ is and i can be either foreground f or background b; P(M i ) is the prior probability of the model M i ; P(y|M i ) is the likelihood of seeing the pixel value y given the model M i ; P(M i |y) is the posterior of the model M i given the pixel value y; P(x|Φ, p, M i ) is the likelihood of the pixel location x given the shape Φ, the pose p and the model M i; P(Φ) is prior probability of the shape Φ; P(p) is the prior probability of the pose p; P(x) is the probability of pixel location x; P(Φ, p|x, y) is the posterior probability of the shape Φ and the pose p given the pixel location x and the pixel value y.