EEG2Face Query: Retrieving Facial Imagery from EEG Signals with Latent Embeddings

Electroencephalography (EEG) has been widely applied in various fields, such as controlling robotic arms for individuals with disabilities and analyzing patients' emotions and mental states. One interesting application is using EEG signals for image retrieval in databases based on human thoughts. This project focuses on enhancing the efficiency of facial image retrieval based on users' mental imagery by utilizing EEG signals. It utilizes the Ultracortex Mark IV headset equipped with 16 sensor points, combined with machine learning techniques, to retrieve facial images that match the user's thoughts. This approach demonstrates the potential of EEG signals in bridging the gap between thought processes and image retrieval, offering new advancements in neuroscience and technology.