The goal of this research is to recognize an object and its orientation in space by using stereo camera. The principle of object orientation recognition in this paper was based on the Scale Invariant Feature Transform (SIFT) and Support Vector Machine (SVM). SIFT has been successfully implemented on object recognition but it had a problem recognizing the object orientation. For many autonomous robotics applications, such as using a vision-guided industrial robot to grab a product, not only correct object recognition will be needed in this process but also object orientation recognition is required. In this paper we used SVM to recognize object orientation. SVM has been known as a promising method for classification accuracy and its generalization ability. The stereo camera system adopted in this research provided more useful information compared to single camera one. The object orientation recognition technique was implemented on an industrial robot in a real application. The proposed camera system and recognition algorithms were used to recognize a specific object and its orientation and then guide the industrial robot to perform some alignment operations on the object.
['Chyi-Yeu Lin', 'Edwin Setiawan']
Object orientation recognition based on SIFT and SVM by using stereo camera