TY - GEN
T1 - An easy-to-implement Benchmarking Tool for Mobile Tablet-PC Visual Pose Estimation
AU - Zhang, Xiaoqiang
AU - Zhang, Yanning
AU - Yang, Tao
AU - Chen, Ting
AU - Yang, Yee Hong
N1 - Publisher Copyright:
© Copyright 2015 ACM .
PY - 2015/12/11
Y1 - 2015/12/11
N2 - Recently, researchers are interested in mobile device based computer vision applications. An accurate visual pose es-timation is a common and important subtask. To quan-titatively evaluate the accuracy, ground truth visual pose datasets are needed. However, the lack of inexpensive and easy benchmarking tool for mobile device based visual poses estimation makes it di-cult, if not impossible, to quantita-tively evaluate the estimated visual poses. In this paper, a novel and easy-to-implement experimental setup is pro-posed to generate ground truth visual pose data for hand-held tablet-PC. The tablet-PC screen is leveraged to display a calibration pattern every time the on-board camera cap-tures an image. The tablet-PC screen image is captured by another camera and is used to estimate the visual pose of the tablet-PC. An experimental environment is setup for param-eter calibration and pose accuracy veri-cation. Extensive experimental results with quantitative analysis demonstrate the accuracy and the generality of our tool.
AB - Recently, researchers are interested in mobile device based computer vision applications. An accurate visual pose es-timation is a common and important subtask. To quan-titatively evaluate the accuracy, ground truth visual pose datasets are needed. However, the lack of inexpensive and easy benchmarking tool for mobile device based visual poses estimation makes it di-cult, if not impossible, to quantita-tively evaluate the estimated visual poses. In this paper, a novel and easy-to-implement experimental setup is pro-posed to generate ground truth visual pose data for hand-held tablet-PC. The tablet-PC screen is leveraged to display a calibration pattern every time the on-board camera cap-tures an image. The tablet-PC screen image is captured by another camera and is used to estimate the visual pose of the tablet-PC. An experimental environment is setup for param-eter calibration and pose accuracy veri-cation. Extensive experimental results with quantitative analysis demonstrate the accuracy and the generality of our tool.
KW - Benchmarking Tool
KW - Smart Mobile Device
KW - Tablet-PC
KW - Visual Pose Estimation
UR - http://www.scopus.com/inward/record.url?scp=84968756392&partnerID=8YFLogxK
U2 - 10.1145/2837126.2837144
DO - 10.1145/2837126.2837144
M3 - 会议稿件
AN - SCOPUS:84968756392
T3 - 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings
SP - 104
EP - 107
BT - 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings
A2 - Khalil, Ismail
A2 - Steinbauer, Matthias
A2 - Chen, Liming
A2 - Anderst-Kotsis, Gabriele
PB - Association for Computing Machinery, Inc
T2 - 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015
Y2 - 11 December 2015 through 13 December 2015
ER -