In this video you can get started with detecting forgeries in videos by learning optical flow analysis: and your instructor, Raahat Devender Singh, has made it really easy to understand. If you wanted to get into digital media forensics, this is a must-watch! And if you like it, don't forget to check out the whole course here. For now, let's jump into this one :)
This course is dedicated to the comprehensive examination of all aspects of the domains of image and video anti–forensics and counter anti–forensics. The participants will gain a deep understanding of these highly consequential research domains, beginning with an introduction to the field of digital image and video forensics, the known kinds of image and video forgeries, the existing literature pertaining to the developments in the domain of forgery detection, and the various issues and challenges that complicate the task of forensic analysis of digital images and videos and impose restrictions on the extent of success of contemporary forensic solutions in heterogeneous real–world situations.
The participants will learn about the process of forensic analysis of video evidence, including integrity verification, source authentication, and content authentication. The participants will also learn about the origin and history of deepfakes and take some time to examine some famous fake videos posted on YouTube. This will be an enjoyable exercise for the participants and will also enable them be more critical of the content we have become so accustomed to consume and inherently believe in our daily lives. This discussion will be followed by a detailed analysis of existing image and video anti–forensic and counter anti–forensic strategies, and will be concluded with an examination of the current research gaps, open issue and future research avenues in this domain. Altogether, this course will enable the participants to establish a strong foundation for personal growth and the eventual development of a meaningful career in the tremendously exciting domain of digital visual media forensics.
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