6. An apparatus for compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: a receiver of visual descriptors extracted from at least one image, said visual descriptors describing key points in images; a processor, configured to determine model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; a quantizer of said model parameters; an encoder of said quantized model parameters; a quantizer of said extracted visual descriptors; and an encoder for encoding said quantized extracted visual descriptors using said model parameters by applying a model based arithmetic encoding to exploit redundancy of the visual descriptors within the at least one image for compression of the visual descriptors.
6. An apparatus for compressing visual descriptors from at least one image by exploiting redundancy of natural image descriptors, comprising: a receiver of visual descriptors extracted from at least one image, said visual descriptors describing key points in images; a processor, configured to determine model parameters of a generative probabilistic model from the extracted visual descriptors in a maximum likelihood sense; a quantizer of said model parameters; an encoder of said quantized model parameters; a quantizer of said extracted visual descriptors; and an encoder for encoding said quantized extracted visual descriptors using said model parameters by applying a model based arithmetic encoding to exploit redundancy of the visual descriptors within the at least one image for compression of the visual descriptors. 7. The apparatus of claim 6 , wherein at least one output of the model parameters and encoded visual descriptors encoders are stored.