TY - GEN
T1 - More improved robust orthogonal iterative algorithm for pose estimation in AR
AU - Ma, Jin Tao
AU - Zhou, Ya
AU - Liu, Wei
AU - Hao, Qun
PY - 2008
Y1 - 2008
N2 - Estimation of camera pose is an integral part and classical problem of augmented reality (AR) system and computer vision. Accurate pose estimation is crucial in determining the rigid transformation relating 2D images to known 3D geometry. Therefore, the algorithm should be not only fast and accuracy, but also robust in AR system. Orthogonal iterative (OI) algorithm is a good method, but it requires a proper initialization and cannot deal with problems of pose ambiguity. A new method based on OI we presented before, provides a good initialization and solves a problem of pose ambiguity introduced by coplanar markers. However, two more potential problems usually make the algorithm calculate some wrong results, and lead to the algorithm unsteady and not robust. In this paper, we develop the method by resolving pose ambiguities, which originate from potential problems in algorithm. Two more constraints are employed in our method. One is camera must be located in front of the marker, while the other is camera must be oriented to the marker. It's proved that the improved method is steady in experiments, and can calculate the pose of camera fast and correctly. Moreover, since the method can deal with pose ambiguity, it is rather robust in AR system.
AB - Estimation of camera pose is an integral part and classical problem of augmented reality (AR) system and computer vision. Accurate pose estimation is crucial in determining the rigid transformation relating 2D images to known 3D geometry. Therefore, the algorithm should be not only fast and accuracy, but also robust in AR system. Orthogonal iterative (OI) algorithm is a good method, but it requires a proper initialization and cannot deal with problems of pose ambiguity. A new method based on OI we presented before, provides a good initialization and solves a problem of pose ambiguity introduced by coplanar markers. However, two more potential problems usually make the algorithm calculate some wrong results, and lead to the algorithm unsteady and not robust. In this paper, we develop the method by resolving pose ambiguities, which originate from potential problems in algorithm. Two more constraints are employed in our method. One is camera must be located in front of the marker, while the other is camera must be oriented to the marker. It's proved that the improved method is steady in experiments, and can calculate the pose of camera fast and correctly. Moreover, since the method can deal with pose ambiguity, it is rather robust in AR system.
KW - Augmented reality
KW - Orthogonal iterative
KW - Pose ambiguity
KW - Pose estimation
UR - http://www.scopus.com/inward/record.url?scp=43649083161&partnerID=8YFLogxK
U2 - 10.1117/12.791589
DO - 10.1117/12.791589
M3 - Conference contribution
AN - SCOPUS:43649083161
SN - 9780819467652
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - International Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing
T2 - International Symposium on Photoelectronic Detection and Imaging 2007 - Image Processing
Y2 - 9 September 2007 through 12 September 2007
ER -