TY - GEN
T1 - Camera pose estimation of a smartphone at a field without interest points
AU - Miyano, Ruiko
AU - Inoue, Takuya
AU - Minagawa, Takuya
AU - Uematsu, Yuko
AU - Saito, Hideo
PY - 2013
Y1 - 2013
N2 - An Augmented Reality (AR) system on mobile phones has recently attracted attention because smartphones have increasingly been popular. For an AR system, we have to know a camera pose of a smartphone. A sensor-based method is one of the most popular ways to estimate the camera pose, but it cannot estimate an accurate pose. A vision-based method is another way to estimate the camera pose, but it is not suitable to a scene with few interest points such as a sports field. In this paper, we propose a novel method of a camera pose estimation for a scene without interest points by combining a sensor-based and a vision-based approach. In our proposed method, we use an acceleration and a magnetic sensor to roughly estimate a camera pose, then search the accurate pose by matching a captured image with a set of reference images. Our experiments show that our proposed method is accurate and fast enough to apply a real-time AR system.
AB - An Augmented Reality (AR) system on mobile phones has recently attracted attention because smartphones have increasingly been popular. For an AR system, we have to know a camera pose of a smartphone. A sensor-based method is one of the most popular ways to estimate the camera pose, but it cannot estimate an accurate pose. A vision-based method is another way to estimate the camera pose, but it is not suitable to a scene with few interest points such as a sports field. In this paper, we propose a novel method of a camera pose estimation for a scene without interest points by combining a sensor-based and a vision-based approach. In our proposed method, we use an acceleration and a magnetic sensor to roughly estimate a camera pose, then search the accurate pose by matching a captured image with a set of reference images. Our experiments show that our proposed method is accurate and fast enough to apply a real-time AR system.
UR - http://www.scopus.com/inward/record.url?scp=84875978325&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875978325&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-37484-5_44
DO - 10.1007/978-3-642-37484-5_44
M3 - Conference contribution
AN - SCOPUS:84875978325
SN - 9783642374838
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 545
EP - 555
BT - Computer Vision - ACCV 2012 International Workshops, Revised Selected Papers
T2 - 11th Asian Conference on Computer Vision, ACCV 2012
Y2 - 5 November 2012 through 9 November 2012
ER -