Patent ID: 8340451

Claim:
A method for constructing an image database that is used for object recognition comprising the steps of: extracting, from an image showing an object and to be stored in the image database, a plurality of local descriptors each of which is a vector representing respective local features of the image; scalar-quantizing the vector on a dimension by dimension basis of the vector; and storing into the image database the image and the corresponding scalar-quantized vectors, with (1) calculating an index value for referring to a bin of a hash table from each scalar-quantized vector by using a predetermined hash function, and (2) storing (i) the value of each scalar-quantized vector dimension and (ii) an image ID for identifying the image from which each vector is extracted into the bin referred to with use of the calculated index value as an entry; wherein each of the steps is executed by a computer and the storing step stores each vector so that, when an image showing an object in question is given as a query while a plurality of images are stored in the image database, the computer extracts a plurality of query local descriptors from the query through a similar step to the feature extraction step, quantizes each query local descriptor through a similar step to the scalar quantization step, retrieves vectors as neighbor vectors of each query local descriptor, each of which is retrieved from the vectors stored in the image database by using an algorithm of approximate nearest neighbor searching, obtains the image IDs attached to the neighbor vectors and determines at least one image(s) which shows the object in question based on the obtained image IDs; and wherein the scalar quantization step quantizes each vector dimension into a scalar number of 8 bits or less and 1 bit or more.