Image recognition method and image recognition apparatus

A method for recognizing a category and a position of a target object included in an image, comprising:

• holding a dictionary in which, for each of a plurality of partial learning images each of which is part of a learning image for recognizing the target object, a category of the partial learning image and position information of the partial learning image are registered, the category and the position information of the partial learning image being classified based on a comparison result of pixel values obtained from a plurality of pixels in the partial learning image and the position information representing information on a relative position between the target object and the partial learning image in the learning image;
• obtaining the target image including the target object which belongs to at least one category of a plurality of categories;
• obtaining a plurality of partial target images from the obtained target image;
• acquiring a plurality of pixel values, from each of the obtained plurality of partial target images, of positions corresponding to the positions where the plurality of pixel values are obtained from each of the partial learning images;
• comparing the plurality of acquired pixel values to each other;
• obtaining from the dictionary, for each of the plurality of partial target images, a corresponding category and the position information of the partial learning image, based on a result of the comparison;
• voting, for each of the plurality of partial target images, the obtained result at a position indicated by the obtained position information by the in a voting surface corresponding to the obtained category of a plurality voting surfaces corresponding to the plurality of categories, and
• recognizing a category and a position of the target object included in the target image by collecting a result of voting.

A non-transitory computer-readable storage medium storing a computer program for causing a computer to execute a method comprising:

• obtaining a target image including a target object which belongs to at least one category of a plurality of categories;
• obtaining a plurality of partial target images from the obtained target image;
• holding a dictionary in which, for each of a plurality of partial learning images each of which is a part of a learning image for recognizing the target object, a category of the partial learning image and position information of the partial learning image are registered, the category and the position information of the partial learning image being classified based on a comparison result of pixel values obtained from a plurality of pixels in the partial learning image, and the position information representing information on a relative position between the target object and the partial learning image in the learning image;
• acquiring a plurality of pixel values, from each of the obtained plurality of partial target images, of positions corresponding to the positions where the plurality of pixel values are obtained from each of the partial learning images;
• comparing the plurality of acquired pixel values to each other;
• obtaining from the dictionary, for each of the plurality of partial target images, a corresponding category and position information of the partial learning image, based on a result of the comparing;
• voting, for each of the plurality of partial target images, the obtained result at a position indicated by the obtained position information in a voting surface corresponding to the obtained category of a plurality voting surfaces corresponding to the plurality of categories, and
• recognizing a category and a position of the target object included in the target image by collecting a result of voting.