Handbook of Digital Face Manipulation and Detection
This handbook represents the first comprehensive collection of research topics in the field of digital face manipulation and detection by a wide variety of experts from various research areas including computer vision, pattern recognition, biometrics and media forensics, among others. While being of...
| Autores: | , , , |
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| Tipo de recurso: | libro |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/711797 |
| Acceso en línea: | http://hdl.handle.net/10486/711797 https://dx.doi.org/10.1007/978-3-030-87664-7 |
| Access Level: | acceso abierto |
| Palabra clave: | DeepFakes Face Manipulation Detection Media Forensic Biometric Recognition Image Processing and Pattern Recognition Open Access Telecomunicaciones |
| Sumario: | This handbook represents the first comprehensive collection of research topics in the field of digital face manipulation and detection by a wide variety of experts from various research areas including computer vision, pattern recognition, biometrics and media forensics, among others. While being of primary interest to researchers in said fields, it appeals to a broad readership by providing detailed theoretical explanations to fundamentals as well as in-depth investigations of current research topics along with comprehensive experimental evaluations. In Part I of this handbook, the reader is provided with introductory overview chapters focusing on the topics of face image and video manipulations and detection (Chap. 1), the impact of different manipulations and alteration methods on face recognition systems (Chap. 2) and general multimedia forensics before the deep learning era (Chap. 3). These chapters serve as points of entry addressing readers wishing to gain a brief overview of the current state of the art. Part II deals with the generation of manipulated face content and its security implications on face recognition, including DeepFakes (Chaps. 4 and 5), face morphing (Chap. 6), adversarial face images (Chap. 7) and audio-to-video face generation (Chap. 8). Subsequently, Part III elaborates on face manipulation detection techniques, containing dedicated chapters on different state-of-the-art detection methods for synthetically generated face images (Chap. 9), DeepFakes videos (Chaps. 10– 14), morphed face images (Chaps. 15 and 16) and retouched face images (Chap. 17). Chapters in Part II and III delve deeper into the topics of digital face manipulation and detection and are oriented towards advanced readers. Eventually, Part IV focuses on further topics including the use of face manipulation for privacy enhancement and the detection thereof (Chap. 18), practical challenges of face manipulation in remote scenarios (Chap. 19) as well as social and ethical issues (Chap. 20). Finally, in a concluding chapter authored by different contributors to this handbook, open research problems and future trends are summarised (Chap. 21). We would like to express our thanks to the editors of the Springer book series Advances in Computer Vision and Pattern Recognition. We also would like to thank all of the authors for the smooth cooperation and their excellent contributions to this handbook |
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