Name
Abstract | ||
|---|---|---|
Corneal reflection extracted from an eye image identifies the relationship between the subject of the image and the scene in front of the subject. The reconstructed scene from corneal reflection provides detailed information about the environment opposite to the subject. It also provides scrutiny about any critical scenario, a subject is encountered with. This research area has significant applications in computer vision, human-computer interaction, psychology, and image forgery detection. Digital image processing and computer vision techniques have been used to reconstruct the scene from cornea image. The proposed model involved the following steps, i.e., identification of the corneal area in an eye, unnecessary reflection removal from cornea surface, developing eye geometric model to correct the spherical effect of the eye, and implementation of super-resolution (SR) algorithm to reconstruct the lost visual information present in the environment. The proposed study is able to reconstruct the SR scene image from cornea image. The effectiveness of the study is evaluated by using subjective as well as objective evaluation measures. Some useful insights related to cornea reflection construction have been described to make this study more effective. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s11042-020-10409-3 | MULTIMEDIA TOOLS AND APPLICATIONS |
Keywords | DocType | Volume |
Cornea reflection, Scene reconstruction, Super resolution, Generative adversarial network | Journal | 80 |
Issue | ISSN | Citations |
14 | 1380-7501 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maimoona Rafiq | 1 | 0 | 0.34 |
| Usama Ijaz Bajwa | 2 | 13 | 5.04 |
| Ghulam Gilanie | 3 | 0 | 1.01 |
| Waqas Anwar | 4 | 0 | 0.34 |