Generic object-based image recognition apparatus with exclusive classifier, and method for the same

An image recognition apparatus for generic object recognition, comprising:

• an identification unit identifying one or more objects contained in an input image by calculating existence probabilities of candidate objects by using LASSO (Least Absolute Shrinkage and Selection Operator) prediction with reference to feature information, the feature information defining visual features of various objects;
• and
• an information accumulating unit accumulating therein exclusive relationship information, the exclusive relationship information defining one or more exclusive object sets each containing different objects predicted not to coexist in a same image, wherein
• the identification unit adjusts the existence probabilities by using the exclusive relationship information, and
• the adjustment is performed by setting a penalty value to a LASSO regularization parameter and thereby lowering existence probabilities of candidate objects that match any of the exclusive object sets defined by the exclusive relationship information.

An image recognition method for generic object recognition, comprising:

• an information accumulating step of accumulating exclusive relationship information, the exclusive relationship information defining one or more exclusive object sets each containing different objects predicted not to coexist in a same image;
• and
• an identification step of identifying one or more objects contained in an input image by calculating existence probabilities of candidate objects by using LASSO (Least Absolute Shrinkage and Selection Operator) prediction with reference to feature information, the feature information defining visual features of various objects, wherein
• through the calculation performed in the identification step, the existence probabilities are adjusted by using the exclusive relationship information, and
• the adjustment is performed by setting a penalty value to a LASSO regularization parameter and thereby lowering existence probabilities of candidate objects that match any of the exclusive object sets defined by the exclusive relationship information.

A computer program used by an image recognition apparatus for generic object recognition, causing a computer to perform:

• an information accumulating step of accumulating exclusive relationship information, the exclusive relationship information defining one or more exclusive object sets each containing different objects predicted not to coexist in a same image;
• and
• an identification step of identifying one or more objects contained in an input image by calculating existence probabilities of candidate objects by using LASSO (Least Absolute Shrinkage and Selection Operator) prediction with reference to feature information, the feature information defining visual features of various objects, wherein
• through the calculation performed in the identification step, the existence probabilities are adjusted by using the exclusive relationship information, and
• the adjustment is performed by setting a penalty value to a LASSO regularization parameter and thereby lowering existence probabilities of candidate objects that match any of the exclusive object sets defined by the exclusive relationship information. cm 18. An integrated circuit used in an image recognition apparatus for generic object recognition, comprising:
• an identification unit identifying one or more objects contained in an input image by calculating existence probabilities of candidate objects by using LASSO (Least Absolute Shrinkage and Selection Operator) prediction with reference to feature information, the feature information defining visual features of various objects;
• and
• an information accumulating unit accumulating therein exclusive relationship information, the exclusive relationship information defining one or more exclusive object sets each containing different objects predicted not to coexist in a same image, wherein
• the identification unit adjusts the existence probabilities by using the exclusive relationship information, and
• the adjustment is performed by setting a penalty value to a LASSO regularization parameter and thereby lowering existence probabilities of candidate objects that match any of the exclusive object sets defined by the exclusive relationship information.