Estimating 3D pose of a known object from a given 2D image is an important problem with numerous studies for robotics and augmented reality applications. While the state-of-the-art Perspective-n-Point algorithms perform well in pose estimation, the success hinges on whether feature points can be extracted and matched correctly on targets with rich texture. In this work, we propose a robust direct method for 3D pose estimation with high accuracy that performs well on both textured and textureless planar targets. First, the pose of a planar target with respect to a calibrated camera is approximately estimated by posing it as a template matching problem. Next, the object pose is further refined and disambiguated with a gradient descent search scheme. Extensive experiments on both synthetic and real datasets demonstrate the proposed direct pose estimation algorithm performs favorably against state-of-the-art feature-based approaches in terms of robustness and accuracy under several varying conditions.
|Title of host publication||2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2016 May 23|
|Event||IEEE Winter Conference on Applications of Computer Vision, WACV 2016 - Lake Placid, United States|
Duration: 2016 Mar 7 → 2016 Mar 10
|Name||2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016|
|Conference||IEEE Winter Conference on Applications of Computer Vision, WACV 2016|
|Period||16/3/7 → 16/3/10|
Bibliographical notePublisher Copyright:
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Computer Vision and Pattern Recognition