5. The method according to claim 1 , wherein the global information used in the second filtering step of the second recognition step comprises the following measurements: measurements of probabilities of co-occurrences between products, measurements of probabilities of vertical positioning of the products, measurements of frequency of the products, previously estimated on a base of planograms.
5. The method according to claim 1 , wherein the global information used in the second filtering step of the second recognition step comprises the following measurements: measurements of probabilities of co-occurrences between products, measurements of probabilities of vertical positioning of the products, measurements of frequency of the products, previously estimated on a base of planograms. 6. The method according to claim 5 , wherein in the second filtering step of the second recognition step, the integration of said global information with the detection results issuing from the second classification step comprises the following steps: a step of estimation of the probabilities that is independent for each of the probability measurements defined in the global information, a parameterised probabilistic combination step where the parameters are previously determined by optimisation of a global recognition level.