Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.13889 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912201528311808 |
|---|---|
| author | Tandon, Abhishek Sharma, Geetanjali Jaswal, Gaurav Nigam, Aditya Ramachandra, Raghavendra |
| author_facet | Tandon, Abhishek Sharma, Geetanjali Jaswal, Gaurav Nigam, Aditya Ramachandra, Raghavendra |
| contents | We propose a trait-specific image generation method that models forehead creases geometrically using B-spline and Bézier curves. This approach ensures the realistic generation of both principal creases and non-prominent crease patterns, effectively constructing detailed and authentic forehead-crease images. These geometrically rendered images serve as visual prompts for a diffusion-based Edge-to-Image translation model, which generates corresponding mated samples. The resulting novel synthetic identities are then used to train a forehead-crease verification network. To enhance intra-subject diversity in the generated samples, we employ two strategies: (a) perturbing the control points of B-splines under defined constraints to maintain label consistency, and (b) applying image-level augmentations to the geometric visual prompts, such as dropout and elastic transformations, specifically tailored to crease patterns. By integrating the proposed synthetic dataset with real-world data, our method significantly improves the performance of forehead-crease verification systems under a cross-database verification protocol. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_13889 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Generating Realistic Forehead-Creases for User Verification via Conditioned Piecewise Polynomial Curves Tandon, Abhishek Sharma, Geetanjali Jaswal, Gaurav Nigam, Aditya Ramachandra, Raghavendra Computer Vision and Pattern Recognition We propose a trait-specific image generation method that models forehead creases geometrically using B-spline and Bézier curves. This approach ensures the realistic generation of both principal creases and non-prominent crease patterns, effectively constructing detailed and authentic forehead-crease images. These geometrically rendered images serve as visual prompts for a diffusion-based Edge-to-Image translation model, which generates corresponding mated samples. The resulting novel synthetic identities are then used to train a forehead-crease verification network. To enhance intra-subject diversity in the generated samples, we employ two strategies: (a) perturbing the control points of B-splines under defined constraints to maintain label consistency, and (b) applying image-level augmentations to the geometric visual prompts, such as dropout and elastic transformations, specifically tailored to crease patterns. By integrating the proposed synthetic dataset with real-world data, our method significantly improves the performance of forehead-crease verification systems under a cross-database verification protocol. |
| title | Generating Realistic Forehead-Creases for User Verification via Conditioned Piecewise Polynomial Curves |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.13889 |