Generating facial morphs through PCA and VAE

Morphing attacks currently are a threat to face identification systems, which is why various morph detection systems are being investigated. The most-used method for morphing is the landmark-based method. Therefore, it is possible that novel morph detection systems are overfitted to detect landmark-based morphs. This research addresses methods to construct fundamentally different morphs using latent spaces. One approach uses Principal Component Analysis (PCA) for generating morphs. We found that PCA is not suitable and explain why. We also used a Variational Auto Encoder (VAE) to create a method for creating morphs through latent spaces which was more successful. The resulting morphs are not convincing enough to fool an existing face recognition system, but they are close. These VAE-based morphs were tested on an existing morph detection system, which was trained on landmark-based morphs, and it was not able to detect any of the novel morphs we created using the VAE-based method.