1. A fusion-based method of object recognition comprising: capturing a first object image with a first image capture detector; generating a first score indicative of a first probability that the first object image corresponds to a data base image; and using a processor to apply a Bayesian fusion algorithm to revise the first probability based on a second score of a second object image indicative of a second probability that the second object image corresponds to the data base image, captured by a second image capture detector, other than the first image capture detector, wherein said using a processor to apply the Bayesian fusion algorithm further includes applying a transition model, configured to calculate a transition probability of an object moving from the first image capture detector to the second image capture detector in time t, wherein said time t is the time difference between a capture time of the first object image and a capture time of the second object image to revise the first probability.