Method for training an object recognition model in a computing device

A computing device comprising:

• a communication unit that receives an image acquired through a camera;
• a user input unit that designates an object of interest in the image;
• a processor that generates an object of non-interest by designating at least a portion of a region excluding the object of interest in the image and trains an object recognition model based on the object of interest and the object of non-interest;
• wherein, in case that a first object not designated as the object of interest is recognized as a result of performing object recognition based on the trained object recognition model, the processor changes the first object to the object of non-interest and retrains the object recognition model based on the changed object of non-interest, wherein the processor generates N number of sets of objects of non-interest with different attributes, and
• wherein the N number of sets of objects of non-interest includes a first set of objects of non-interest set randomly designated in the region excluding the object of interest by the processor of the computing device, and
• a plurality of second sets of objects of non-interest sets generated while, among grid regions obtained by dividing the image at a predetermined grid interval, changing the grid interval in the region excluding the object of interest.

A computing device comprising:

• a communication unit that receives an image acquired through a camera;
• a user input unit that receives a user selection of displayed objects in the image and designates an object of interest in the image in accordance with the user selection;
• a processor that generates an object of non-interest by designating randomly selected portion of a region excluding the object of interest in the image and trains an object recognition model based on the object of interest and the object of non-interest;
• wherein, in case that a first object not designated as the object of interest is recognized as a result of performing object recognition based on the trained object recognition model, the processor changes the first object to the object of non-interest and retrains the object recognition model based on the changed object of non-interest.