TY - GEN
T1 - Estimation of camera extrinsic parameters of indoor omni-directional images acquired by a rotating line camera
AU - Oh, Sojung
AU - Lee, Impyeong
PY - 2012
Y1 - 2012
N2 - To use omni-directional images obtained by a rotating line camera for indoor services, we should know the position and attitude of the camera at the acquisition time to register the images with respect to an indoor coordinate system. In this study, we thus develop a method for the estimation of the extrinsic orientation parameters of an omni-directional image. First, we derive a collinearity equation for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the extrinsic orientation parameters (EOP) through the collinearity equations with indoor control points which are stochastic constraints. The experimental results indicate that the extrinsic orientation parameters are estimated with the precision of ±1.4 mm and ±0.05° for the position and attitude, respectively. The residuals are within ±3.11 and ±9.20 pixels in horizontal and vertical directions. Using the proposed method for estimating EOP of indoor omni-directional images, we can generate sophisticated indoor 3D models and offer precise indoor services to users based on the models.
AB - To use omni-directional images obtained by a rotating line camera for indoor services, we should know the position and attitude of the camera at the acquisition time to register the images with respect to an indoor coordinate system. In this study, we thus develop a method for the estimation of the extrinsic orientation parameters of an omni-directional image. First, we derive a collinearity equation for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the extrinsic orientation parameters (EOP) through the collinearity equations with indoor control points which are stochastic constraints. The experimental results indicate that the extrinsic orientation parameters are estimated with the precision of ±1.4 mm and ±0.05° for the position and attitude, respectively. The residuals are within ±3.11 and ±9.20 pixels in horizontal and vertical directions. Using the proposed method for estimating EOP of indoor omni-directional images, we can generate sophisticated indoor 3D models and offer precise indoor services to users based on the models.
UR - http://www.scopus.com/inward/record.url?scp=84866645917&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33191-6_61
DO - 10.1007/978-3-642-33191-6_61
M3 - Conference contribution
AN - SCOPUS:84866645917
SN - 9783642331909
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 616
EP - 625
BT - Advances in Visual Computing - 8th International Symposium, ISVC 2012, Revised Selected Papers
T2 - 8th International Symposium on Visual Computing, ISVC 2012
Y2 - 16 July 2012 through 18 July 2012
ER -