Within this blog post you will discover what the golden ratio is and how you can construct your own golden rectangle. However if you want to improve your compositions, the golden ratio is a worth learning. With all of these questions it can become confusing. Where do I place my focal point? Where do I arrange the composition? Where do I even begin? However, especially for beginners, it can be challenging. 1–12 (2021).Creating a dynamic composition can vastly improve your art. Sudhakar, K., Nithyanandam, P.: Facial identification of twins based on fusion score method. Mohammed, B.O.: A multimodal biometric system using global features for identical twins identification. (eds.) Advances in Automation, Signal Processing, Instrumentation, and Control. In: Komanapalli, V.L.N., Sivakumaran, N., Hampannavar, S. Rehkha, K.K., Vinod, V.: A literary survey on multimodal biometric identification of monozygotic twins. The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp) (2015) In: Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV). 11, 1–15 (2017)īao, Y., Yin, Y., Musa, L.: Face recognition and using ratios of face features in gender identification. Hamayun, A.K.: Feature fusion and classifier ensemble technique for robust face recognition. 4(12), 624 (2012)Īlsawwaf, M., et al.: In your face: person identification through ratios and distances between facial features. Packiriswamy, V., Kumar, P., Rao, M.: Identification of facial shape by applying golden ratio to the facial measurements: an interracial study in Malaysian population. Rodriguez, M., Andrea, Z.G., Worring, M.: Likelihood ratios for deep neural networks in face comparison.

Vinay, A., et al.: Unconstrained face recognition using Bayesian classification. In: 2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). Vengatesan, K., et al.: Face recognition of identical twins based on support vector machine classifier. Ounachad, K.: Golden ratio and its application to Bayes classifier based face sketch gender classification and recognition (2020)ĭong, X., et al.: A survey on ensemble learning. Advances in Signal and Data Processing, pp. Gaikwad, P.S., Kulkarni, V.B.: Face Recognition Using Golden Ratio for Door Access Control System. Milutinovic, J., Zelic, K., Nedeljkovic, N.: Evaluation of facial beauty using anthropometric proportions. 7(2), 307–316 (2013)Īlam, M.K., et al.: Multiracial facial golden ratio and evaluation of facial appearance. Hassaballah, M., Murakami, K., Ido, S.: Face detection evaluation: a new approach based on the golden ratio. Jan, N., et al.: Identification of facial shape by applying golden ratio in ethnic Kashmiri populationĭey, A., et al.: A hybrid meta-heuristic feature selection method using golden ratio and equilibrium optimization algorithms for speech emotion recognition. Hwang, K., Park, C.Y.: The divine proportion: origins and usage in plastic surgery. IEEE (2016)Īnand, S., et al.: Vertical and horizontal proportions of the face and their correlation to phi among Indians in Moradabad population: a survey. In: 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE (2017)ĭhimar, T., Mistree, K.: Feature extraction for facial age estimation: a survey. In: 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). Prema, R., Shanmugapriya, P.: A review: face recognition techniques for differentiate similar faces and twin faces.

Taskiran, M., Kahraman, N., Erdem, C.E.: Face recognition: past, present and future (a review). Moung, E.G., et al.: Face recognition state-of-the-art, enablers, challenges and solutions: a review. Kukharev, G.A., Kaziyeva, N.: Digital facial anthropometry: application and implementation. Rustam, Z., Faradina, R.: Face recognition to identify look-alike faces using support vector machine. Mousavi, S., Charmi, M., Hassanpoor, H.: Recognition of identical twins based on the most distinctive region of the face: human criteria and machine processing approaches. In: 2019 IEEE Globecom Workshops (GC Wkshps). (IJLTEMAS) (2018)Īhmad, B., et al.: Deep convolutional neural network using triplet loss to distinguish the identical twins. Chijindu, A.T., Chinagolum, I.: Machine learning based digital recognition of identical twins to support global crime investigation.

Goldenratio faces