Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Real-Time Non-Rigid Surface Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Shape matching and object recognition
Shape matching and object recognition
Homography-based 2D Visual Tracking and Servoing
International Journal of Robotics Research
Tracking by an Optimal Sequence of Linear Predictors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
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This paper presents a template matching approach to high accuracy detection and tracking of perspectively distorted objects. To this end we propose a robust match metric that allows significant perspective shape changes. Using a coarse-to-fine representation for the detection of the template further increases efficiency. Once an template is detected at interactive frame-rate, we immediately switch to tracking with the same algorithm, enabling detection times of only 20ms. We show in a number of experiments that the presented approach is not only fast, but also very robust and highly accurate in detecting the 3D pose of planar objects or planar subparts of non-planar objects. The approach is used in augmented reality applications that could up to now not be sufficiently solved, because existing approaches either needed extensive training data, like machine learning methods, or relied on interest point extraction, like descriptors-based methods.