Notice: If you are not a student of the Department of Informatics or the Department of Electrical Engineering and Information Technology of the Karlsruhe Institute of Technology, you are responsible to find a professor who will supervise you.
Master Thesis, Johanna Thiemich, 2021
This master’s thesis deals with the topic of detecting human abnormal behavior in surveillance videos in urban scenarios. In order to differentiate between normal and abnormal behavior, only sequences of human pose skeletons are considered … Read more
Bachelor Thesis, Claudius Kienle, 2021
At large events, video-based analysis tools on crowds are an emerging technology to support local security forces monitor the situation. However, the computations involved are extremely resource-intensive, which hinders on-site use on … Read more
Bachelor Thesis, Calvin Kramer, 2020
Due to ongoing population growth and the resulting increase in cities’ densities, we are facing a world in which blank space becomes less common and crowded areas the everyday standard of many people’s life. Although foot traffic is a well-known size in urban planning, bottlenecks cannot … Read more
Master Thesis, Xiaoyan Kong, 2020
The problem of human pose estimation in the field of video surveillance is tougher than for classical scenarios. This difference comes from many people at small scale, which is accompanied by lots of ambiguities and occlusions. Typically, one would train a network on suited data to improve the performance. However such … Read more
Master Thesis, Florian Krüger, 2020
Through crowd density estimation, an estimate for the number of individuals in an image can be obtained. State-of-the-art methods yield precise estimates by utilizing deep learning architectures exclusively. Aerial imagery is … Read more
Bachelor Thesis, Oliver Becker, 2020
Due to the great advances in machine learning, many complex problems now become tractable. One such problem is pose estimation, which has attracted a lot of attention recently. Image-based pose estimation aims … Read more
Bachelor Thesis, Kristina Katovich, 2019
Video-based activity recognition is a research field of broad interest. There exists a variety of methods that tackle this problem, most of which are working directly on image data. However, artificial / synthetic data have already proven their value for various tasks in machine learning. Kristina is therefore ivestigating whether such data can also be applied to the problem of activity recognition. Read more
Master Thesis, Andreas Blattmann, 2019
Pose estimation is a quiet challenging task in the field of crowd monitoring. The promising JTA dataset provides an easy way to generate many poses with annotated ground truth keypoints. However, the gap between synthetical and real data ist quite big, therefore Andreas tries to minimize the distance between both domains. Read more
Master Thesis, Nils Murzyn, 2019
Anomaly detection plays an important role in a wide range of applications. In the field of video surveillance, image-based detection of an anomalous situation should be achieved. The requirements for … Read more
Master Thesis, Tobias Kalb, 2019
Human pose estimation has recently made significant progress with the adoption of deep convolutional neural networks and the many applications have attracted tremendous interest in recent years. However … Read more
Bachelor Thesis, Tobias Bleymehl, 2019
Density Based Crowd Couting is getting used more often to further improve the work of various areas in modern society. State-of-the-art methods accomplish better results estimating counts and positions … Read more
Bachelor Thesis, Thomas Dissert, 2018
Body pose estimation with deep learning programs on image-data is a common and heavily studied subtask in computer vision. The objective of this work is to evaluate the current state-of-the-art person pose estimators … Read more