A pipeline for analysing image and video material in a forensic context with intelligent systems

Abstract

Shows like CSI seem to convey a certain view on the capabilities of forensic science based on the vast progress of digitalisation and the new technology, that goes along with it. But those depictions can be misleading and hardly represent a realistic reflection of reality. Nevertheless, this representation influences the public view on digital forensic analysis. This phenomenon is also known as the CSI effect. To present a more realistic view on practices in digital forensics, we want to introduce typical image and video analysis methods used in tackling real life forensic challenges and point to their capabilities as well as their limits. In this context an important area is image and video enhancement. With methods such as Super Resolution, images can be scaled up, their corresponding resolution gets enhanced and image noise can be reduced. During the subsequent image analysis, methods ranging from purely cognitive analysis to extraction of raw pixel values and various semantic information from the image or video, utilizing AI frameworks, are used. This allows for example to detect and analyse faces up to whole people, as well as objects in images or videos.