A Deep Learning Model on Face Matching

A Deep Learning Model on Face Matching

Mayank Tripathi¹, Richa Singh², Shambhavi Srivastava³ Pawan Mishra⁴

¹Mayank Tripathi CSE department ITM Gida Gorakhpur

²Richa Singh CSE department ITM Gida Gorakhpur

³Shambhavi Srivastava CSE department ITM Gida Gorakhpur

⁴Pawan Mishra CSE department ITM Gida Gorakhpur

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Abstract -This study provides an overview of the Face Matching Model (FMM) stages, methods, and datasets that are currently available. A crucial topic in the realms of computer vision and Deep learning, FMM has been acknowledged for decades. The majority of applications, including those in healthcare, education, criminal investigation, etc., benefit from automatic FMM. This essay seeks to comprehend the fundamental ideas behind FMM and to contrast recent findings. Recognition of face Recognition has recently become a crucial topic in many applications. The study of facial expression recognition has grown significantly in recent years. Face recognition identification attempts to determine a person's face state (such as Fake or Real Images) based on specific facial images. Expression of Individuals is crucial in communication, which enhances the standard of human contact. In the near future, the research of face detection may also improve social feedback and interactions between Human Robot Interfaces (HRI). The geometric portion of the face is mostly used for identity detection (eg; eyes, lips, mouth and nose).

Key Words: Deep Learning, Face Matching, Video Surveillance and Security purposes etc.