Stable Real-Time 3D Tracking Using Online and Offline Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Fast Keypoint Recognition Using Random Ferns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Detection and Tracking for Augmented Reality on Mobile Phones
IEEE Transactions on Visualization and Computer Graphics
Extended Keyframe Detection with Stable Tracking for Multiple 3D Object Tracking
IEEE Transactions on Visualization and Computer Graphics
ORB: An efficient alternative to SIFT or SURF
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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We present a novel 2D-3D matching method, which is applicable to the pose detection of a target 3D object for an AR application. Our method matches 2D keypoints against their corresponding 3D points directly with a classification approach, and implements a matching refinement using geometric restriction. Our method achieves robust matching and handles the problem that the performance of the conventional keyframe-based methods relies on the pose of the target object in reference images due to self-occlusion. In our experiment, our method improved the matching performance of the conventional method by 15 percentage points.