Abstract: Provided is a method for selecting key points for real-time tracking in a mobile environment, which is used by a key point application executed by at least one processor of a computing device to select key points for real-time tracking in a mobile environment. The method comprises obtaining a target object image capturing a target object; extracting a plurality of temporary key points from the obtained target object image; determining confirmed key points by filtering the plurality of extracted temporary key points according to a predetermined distribution criterion; setting the confirmed key points as final key points for the target object image; storing target object tracking information including the final key points set for the target object image; and providing the target object tracking information to an application executing a predetermined function through the target object tracking in a mobile environment.

Abstract: A system for object detection and posture estimation based on an object-customized image feature detection algorithm according to an embodiment of the present disclosure comprises at least one or more processors; and at least one or more memories, wherein at least one application, as an application that is stored in the memory and performs object detection and posture estimation based on an object-customized image feature detection algorithm by being executed by the at least one or more processors, learns a goal object based on a plurality of image feature detection algorithms, generates an algorithm list that includes evaluation of the plurality of image feature detection algorithms for detecting the learned goal object, detects a target object corresponding to the goal object among at least one or more candidate objects within an input image based on the generated algorithm list, and performs a posture estimation process for the detected target object based on the generated algorithm list.