Advanced Portrait Rendering: Algorithmic Creation of Artistic Images

Authors

  • Robert Philip
  • Lindsay Arvey
  • Sian Tai

DOI:

https://doi.org/10.54097/fshsed73

Keywords:

Face Photos; Cartoon Image; Illumination Editing; Non-Photorealistic Rendering.

Abstract

This study introduces a refined algorithm for creating artistic portraits with dynamic, editable lighting effects derived from facial photographs. The proposed method begins by extracting edge contours from the input photo to construct a foundational line drawing. Subsequent steps involve intrinsic decomposition to differentiate between the photo's illumination and reflectance components. The illumination component undergoes a series of edits, including quantization and nonlinear adjustments, to refine its visual impact. Concurrently, the reflectance component is abstracted and merged with the line drawing to form a preliminary cartoon-style image devoid of specific lighting effects. The final artistic rendering is achieved by reintegrating the edited illumination component, resulting in a visually striking cartoon image that preserves realistic lighting dynamics. Experimental evaluations confirm the algorithm's ability to produce high-quality, realistic cartoon images with customizable lighting effects, making it a significant contribution to the fields of non-photorealistic rendering and digital art creation.

References

Hebborn, A., Li, C., & Mould, D. (2022). Cartoonization: A Survey and Taxonomy of Non-photorealistic Rendering for Artistic Stylization. ACM Computing Surveys (CSUR), 55(1), 1-38.

Hebborn, A., Li, C., & Mould, D. (2022). Cartoonization: A Survey and Taxonomy of Non-photorealistic Rendering for Artistic Stylization. ACM Computing Surveys (CSUR), 55(1), 1-38.

Chen, H., Xu, Y., Shum, H. Y., Zhu, S., & Zheng, N. (2018). Example-based facial sketch generation with non-parametric sampling. In Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on (Vol. 2, pp. 433-438). IEEE.

Chen, H., Liu, Z., Rose, C., Xu, Y., Shum, H. Y., & Salesin, D. (2019). Example-based composite sketching of human portraits. In Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering (pp. 95-153).

Chen, H., Zheng, N. N., Liang, L., Li, Y., Xu, Y. Q., & Shum, H. Y. (2022). PicToon: a personalized image-based cartoon system. In Proceedings of the tenth ACM international conference on Multimedia (pp. 171-178).

Yao, Y. (2018). Facial Non-photorealistic Rendering with Adjustable Lighting Effects Based on Photos (Master's thesis, Zhejiang University).

Winnemöller, H., Olsen, S. C., & Gooch, B. (2021). Real-time video abstraction. ACM Transactions On Graphics (TOG), 25(3), 1221-1226.

DeCarlo, D., & Santella, A. (2022). Stylization and abstraction of photographs. In ACM Transactions on Graphics (TOG) (Vol. 21, No. 3, pp. 769-776). ACM.

Guo, H., Ma, Z., Chen, X., Wang, X., Xu, J., & Zheng, Y. (2024). Generating Artistic Portraits with Feature Disentanglement and Reconstruction. Electronics.

Barron, J. T., & Malik, J. (2022). Color constancy, intrinsic images, and shape estimation. In European Conference on Computer Vision (pp. 57-70). Springer, Berlin, Heidelberg.

Barron, J. T., & Malik, J. (2023). Shape, albedo, and illumination from a single image of an unknown object. In 2012 IEEE Conference on Computer Vision and Pattern Recognition (pp. 334-341). IEEE.

Yan, F., Fei, G. Z., Liu, T. T., Shen, J., Wang, R., & Chi, H. (2022). An algorithm for generating cartoon-style facial portrait. Journal of Computer-Aided Design & Computer Graphics, 19(4), 442-447.

Huang, H., & Cheng, W. (2021). Real-time image sketching stylization. Chinese Journal of Computers, 32(10), 2023-2029.

Yi, R., Liu, Y. J., Lai, Y. K., & Rosin, P. L. (2024). APDrawingGAN: Generating artistic portrait drawings from face photos with hierarchical GANs. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10743-10752).

Winnemöller, H., Kyprianidis, J. E., & Olsen, S. C. (2022). XDoG: an eXtended difference-of-Gaussians compendium including advanced image stylization. Computers & Graphics, 36(6), 740-753.

Hebborn, A., Li, C., & Mould, D. (2022). Cartoonization: A Survey and Taxonomy of Non-photorealistic Rendering for Artistic Stylization. ACM Computing Surveys (CSUR), 55(1), 1-38.

Li, X., Wang, X., Chen, X., Lu, Y., Fu, H., & Wu, Y. C. (2024). Unlabeled data selection for active learning in image classification. Scientific Reports, 14(1), 424.

Chen, J., & Liu, G. (2023). AnimeGAN: A novel lightweight GAN for photo animation. In International Symposium on Intelligence Computation and Applications (pp. 242-256). Springer, Singapore.

Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2023). Unpaired image-to-image translation using cycle-consistent adversarial networks. In Proceedings of the IEEE international conference on computer vision (pp. 2223-2232).

Kyprianidis, J. E., Collomosse, J., Wang, T., & Isenberg, T. (2023). State of the "Art": A taxonomy of artistic stylization techniques for images and video. IEEE transactions on visualization and computer graphics, 19(5), 866-885.

Lai, W. S., Huang, J. B., Ahuja, N., & Yang, M. H. (2023). Deep laplacian pyramid networks for fast and accurate superresolution. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4), 2422-2436.

Liang, Y., Wang, X., Wu, Y. C., Fu, H., & Zhou, M. (2023). A Study on Blockchain Sandwich Attack Strategies Based on Mechanism Design Game Theory. Electronics, 12(21), 4417.

Bi, S., Han, X., & Yu, Y. (2022). An L1 image transform for edge-preserving smoothing and scene-level intrinsic decomposition. ACM Transactions on Graphics (TOG), 34(4), 1-12.

Nestmeyer, T., & Gehler, P. V. (2022). Reflectance adaptive filtering improves intrinsic image estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 6789-6798).

Kang, H., Lee, S., & Chui, C. K. (2019). Coherent line drawing. In Proceedings of the 5th international symposium on Non-photorealistic animation and rendering (pp. 43-50).

Tomasi, C., & Manduchi, R. (2019). Bilateral filtering for gray and color images. In Computer Vision, 1998. Sixth International Conference on (pp. 839-846). IEEE.

Barash, D., & Comaniciu, D. (2022). A common framework for nonlinear diffusion, adaptive smoothing, bilateral filtering and mean shift. Image and Vision Computing, 22(1), 73-81.

Wang, X., Wu, Y. C., Ji, X., & Fu, H. (2024). Algorithmic discrimination: examining its types and regulatory measures with emphasis on US legal practices. Frontiers in Artificial Intelligence, 7, 1320277.

Downloads

Published

28-06-2024

Issue

Section

Articles

How to Cite

Philip, R., Arvey, L., & Tai , S. (2024). Advanced Portrait Rendering: Algorithmic Creation of Artistic Images. Mathematical Modeling and Algorithm Application, 2(2), 6-12. https://doi.org/10.54097/fshsed73