Patent ID: 10430691

Abstract:
A method for learning parameters of an object detector based on a CNN adaptable to customers' requirements such as KPI by using a target object merging network and a target region estimating network is provided. The CNN can be redesigned when scales of objects change as a focal length or a resolution changes depending on the KPI. The method includes steps of: a learning device (i) instructing the target region estimating network to search for k-th estimated target regions, (ii) instructing an RPN to generate (k_1)-st to (k_n)-th object proposals, corresponding to an object on a (k_1)-st to a (k_n)-th manipulated images, and (iii) instructing the target object merging network to merge the object proposals and merge (k_1)-st to (k_n)-th object detection information, outputted from an FC layer. The method can be useful for multi-camera, SVM (surround view monitor), and the like, as accuracy of 2D bounding boxes improves.