This paper presents a method of improving the pose recognition accuracy of objects by using Kinect sensor. First, by using the SURF algorithm, which is one of the most widely used local features point algorithms, we modify inner parameters of the algorithm for efficient object recognition. The proposed method is adjusting the distance between the box filter, modifying Hessian matrix, and eliminating improper key points. In the second, the object orientation is estimated based on the homography. Finally the novel approach of Auto-scaling method is proposed to improve accuracy of object pose estimation. The proposed algorithm is experimentally tested with objects in the plane and its effectiveness is validated.

• 김안나(Mechanical Engineering, SungKyunKwan University, Master course) | ANNA KIM
• 이건규(Mechanical Engineering, SungKyunKwan University, Master course) | Gun Kyu Yee
• 강기태(Mechanical Engineering, SungKyunKwan University, Combined course) | Gitae Kang
• 김용범(Mechanical Engineering, SungKyunKwan University, Combined course) | Yong Bum Kim
• 최혁렬(Mechanical Engineering, SungKyunKwan University) | Hyouk Ryeol Choi Corresponding author