Name
Abstract | ||
|---|---|---|
Camera tracking is a fundamental requirement for video-based augmented reality applications. The ability to accurately calculate the intrinsic and extrinsic camera parameters for each frame of a video sequence is essential if synthetic objects are to be integrated into the image data in a believable way. In this paper, we present an accurate and reliable approach to camera calibration for off-line video-based augmented reality applications. We first describe an improved feature tracking algorithm, based on the widely used Kanade-Lucas-Tomasi tracker. Estimates of inter-frame camera motion are used to guide tracking, greatly reducing the number of incorrectly tracked features. We then present a robust hierarchical scheme that merges sub-sequences together to form a complete projective reconstruction. Finally, we describe how RANSAC-based random sampling can be applied to the problem of self-calibration, allowing for more reliable upgrades to metric geometry. Results of applying our calibration algorithms are given for both synthetic and real data. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ISMAR.2002.1115068 | ISMAR |
Keywords | Field | DocType |
extrinsic camera parameter,reliable approach,image data,off-line video-based augmented reality,camera tracking,video-based augmented reality,camera calibration,accurate camera calibration,calibration algorithm,inter-frame camera motion,improved feature tracking algorithm,tracking,calibration,sampling methods,image reconstruction,random sampling,motion estimation,robustness,geometry,augmented reality | Computer vision,Computer graphics (images),Computer science,RANSAC,Camera auto-calibration,Smart camera,Robustness (computer science),Augmented reality,Video tracking,Camera resectioning,Artificial intelligence,Motion estimation | Conference |
ISBN | Citations | PageRank |
0-7695-1781-1 | 38 | 2.24 |
References | Authors | |
21 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simon Gibson | 1 | 230 | 18.68 |
| Jon Cook | 2 | 147 | 13.61 |
| Toby Howard | 3 | 206 | 16.91 |
| Roger J. Hubbold | 4 | 520 | 52.85 |
| Dan Oram | 5 | 38 | 2.24 |