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Conference Paper
Camera Pose Estimation Using Optical Flow and ORB Descriptor in SLAM-Based Mobile AR Game
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- Authors
- Junseong Bang, Dongchun Lee, Yongjun Kim, Hunjoo Lee
- Issue Date
- 2017-02
- Citation
- International Conference on Platform Technology and Service (PlatCon) 2017, pp.234-237
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- A mobile augmented reality (AR) game application was developed based on simultaneous localization and mapping (SLAM). The SLAM-based AR game requires to estimate the pose from the camera input image in real time. Before running the game, point cloud data for a real-world game space is built. While the game is running, the camera pose is estimated by matching the prebuilt point cloud data and camera input image. To minimize errors in the matching, we present a hybrid method using an optical flow and ORB descriptor, where the optical flow accurately tracks the displacement of keypoints in consecutive images, and the ORB is a fast keypoint descriptor under a BSD license. The performance of the hybrid method is compared with a method using only the ORB descriptor matching. In addition, a mobile AR game embedding the hybrid method was tested in both indoor and outdoor environments.
- KSP Keywords
- Augmented reality(AR), Camera pose estimation, Descriptor matching, Indoor and outdoor environments, Keypoint Descriptor, Mobile AR, ORB Descriptor, Optical flow, Point Cloud Data, Real-time, Real-world