Multi-view target searching method based on probability model

The invention discloses a multi-view target searching method based on a probability model. The multi-view target searching method comprises the following steps of extracting Zernike moments of initial view sets of various objects from a multi-view model library to obtain an initial feature vector set; gathering initial feature vectors of all the objects to obtain a total initial feature vector set and defining the total initial feature vector set as a multi-view feature library; randomly selecting an object from the multi-view model library and using the selected object as a query target; selecting an optional object as a comparing target; finding out an object which is similar to the query target from the multi-view model library; performing theoretical analysis to obtain a probability function based on a Gaussian model; performing sample training to obtain model parameters; calculating matching probability of the query target and the comparing target; and arraying the matching probabilities of the query target and all models in the multi-view model library in a descending order to obtain a final searching result. By the multi-view target searching method, dependence on space position information of a camera is avoided when initial views are acquired. The multi-view target searching method can be used for any multi-view target databases based on views.