11. An apparatus for multimedia model retrieval, comprising: at least one hardware processor operable to: acquire parameters of a first multimedia model to be retrieved; generate a projection image from the first multimedia model according to the parameters of the first multimedia model; perform a feature extraction on the projection image to generate a first feature extraction result; compare the first feature extraction result with a plurality of feature extraction results corresponding to a plurality of multimedia models stored in a database so as to obtain a retrieval result, wherein the retrieval result comprises a number of multimedia models; and train a support vector machine with multimedia models labeled by a user upon the retrieval result with a probability value, and perform a probability-based classification on the plurality of multimedia models stored in a database by the support vector machine to obtain a classification result, and update the retrieval result with the classification result.
11. An apparatus for multimedia model retrieval, comprising: at least one hardware processor operable to: acquire parameters of a first multimedia model to be retrieved; generate a projection image from the first multimedia model according to the parameters of the first multimedia model; perform a feature extraction on the projection image to generate a first feature extraction result; compare the first feature extraction result with a plurality of feature extraction results corresponding to a plurality of multimedia models stored in a database so as to obtain a retrieval result, wherein the retrieval result comprises a number of multimedia models; and train a support vector machine with multimedia models labeled by a user upon the retrieval result with a probability value, and perform a probability-based classification on the plurality of multimedia models stored in a database by the support vector machine to obtain a classification result, and update the retrieval result with the classification result. 14. The apparatus according to claim 11 , wherein the at least one hardware processor is further operable to employ the multimedia models manually labeled by a user upon the retrieval result with a probability value as a training sample and train according to the training sample to obtain the support vector machine; and to perform a probability-based classification on the plurality of multimedia models stored in a database by the support vector machine to obtain a classification result, and update the retrieval result with the classification result.