1. Field
Example embodiments of the following disclosure relate to an object recognition, and more particularly, to an object recognition using an analysis of point clouds of an image.
2. Description of the Related Art
With respect to a method of recognizing an object, various methods are being suggested according to characteristics of sensors that are used during the process of object recognition. Among the various methods, an object recognition method that uses information of an image sensor may be largely grouped into two methods. The first method, for example, scale-invariant feature transform (SIFT) or speeded up robust features (SURF), is achieved by extracting a feature point using the brightness value of each pixel of an image, such that a descriptor is generated. The second method is achieved by an edge of an object using the differential of the brightness of an image, such that the shape of an object is inferred and recognized using the edge. The method as such is achieved by acquiring a three-dimensional (3D) point cloud using TOF (Time of Flight) and a laser sensor, in addition to an image sensor to recognize an object based on the acquired 3D point clouds.
Regarding related methods, depending on the characteristic of the algorithm of each method, each method is provided with difficulties. As for the method, such as SIFT and SURF, of recognizing an object by the brightness value, a pattern that is not repeated on the surface of the object is needed to be provided. That is, distinguishing dishes and balls that are used in real life may be difficult. In addition, in a case when an object is largely inclined in an image, the recognition rate is rapidly decreased. The method of extracting the edge of an object, on the contrary, provides a lower object recognition rate as the external shape of the object becomes simpler. In addition, in a case when many lines are extracted due to the complexity of the background of an object, the time of performing the object recognition is rapidly increased. The algorithm using 3D point clouds as well is configured to have only the shape of an object as the characteristic of the object, and thus, the method may not be able to distinguish the objects having similar shapes to each other.
Therefore, there is a need for improved object recognition.