Name
Title | ||
|---|---|---|
High-order Taylor expansion based image space transform method for real-time augmented reality. |
Abstract | ||
|---|---|---|
This paper proposes a real-time augmented reality method based on Taylor expansion formula. This method has the advantage that the pixel relationship in the discrete image space is converted to a continuous high-order Taylor space and maintains pixel invariance. After conversion to Taylor space, the ability to resist dramatic changes in illumination between frames is enhanced and robust to intra-frame local illumination mutations. In the spatial transformation process, differential low-order features are used to represent higher-order features, multiplied by appropriate feature coefficients. These coefficients are first determined theoretically and then experimentally verified, allowing us to obtain high-order feature information and approximate the original pixel values based on the features. We then applied this technique to color-based mean shift tracking problems to achieve promising results. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.comcom.2020.02.002 | Computer Communications |
Keywords | Field | DocType |
Real-time augment reality,Space transformation,Taylor expansion,Tracking | Computer graphics (images),Computer science,Real-time computing,Augmented reality,Taylor series | Journal |
Volume | ISSN | Citations |
153 | 0140-3664 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Feiran Fu | 1 | 1 | 0.69 |
| Fang Ming | 2 | 6 | 2.60 |
| Huamin Yang | 3 | 19 | 17.29 |
| Zhe Li | 4 | 1 | 0.35 |