Abstract: Provided is a method for constructing an image database for object recognition, which includes a feature extraction step of extracting local descriptors from object images which are to be stored in an image database, a scalar quantization step of quantizing a numeric value indicating each dimension of each of the local descriptors into a predetermined number of bit digits, and a storing step of organizing each of the local descriptors after the quantization to be able to be searched for in the closest vicinity, giving to the local descriptor an identifier of the image from which the local descriptor has been extracted, and storing the local descriptor to which the identifiers are given in the image database.

Abstract: Provided are a method of generating a low-capacity model capable of identifying an object with high accuracy, and creating an image database using the model, a processing program for executing the method, and a processing apparatus that executes the process. The method for compiling an image database that is used for a three-dimensional object recognition includes a steps of extracting vectors as local descriptors from a plurality of images each image showing a three-dimensional object as seen from different viewpoints, a model creating step of evaluating the degree of contribution of each local descriptor to identification of the three-dimensional object, and creating a three-dimensional object model systematized to ensure approximate nearest neighbor search using the individual vectors which satisfy criteria, and a registration step of adding an object identifier to the created object model and registering the object model into an image database.