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Automatic Procedural Model Generation for 3D Object Variation


The Visual Computer

3D objects are used for numerous applications. In many cases not only single objects but also variations of objects are needed. Procedural models can be represented in many different forms, but generally excel in content generation. Therefore this representation is well suited for variation generation of 3D objects. However, the creation of a procedural model can be time-consuming on its own. We propose an automatic generation of a procedural model from a single exemplary 3D object. The procedural model consists of a sequence of parameterizable procedures and represents the object construction process. Changing the parameters of the procedures changes the surface of the 3D object. By linking the surface of the procedural model to the original object surface, we can transfer the changes and enable the possibility of generating variations of the original 3D object. The user can adapt the derived procedural model to easily and intuitively generate variations of the original object. We allow the user to define variation parameters within the procedures to guide a process of generating random variations. We evaluate our approach by computing procedural models for various object types, and we generate variations of all objects using the automatically generated procedural model.

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Ulmer, Alex; Sessler, David; Kohlhammer, Jörn

NetCapVis: Web-based Progressive Visual Analytics for Network Packet Captures


VizSec 2019

IEEE Symposium on Visualization for Cyber Security (VizSec) <16, 2019>

Network traffic log data is a key data source for forensic analysis of cybersecurity incidents. Packet Captures (PCAPs) are the raw information directly gathered from the network device. As the bandwidth and connections to other hosts rise, this data becomes very large quickly. Malware analysts and administrators are using this data frequently for their analysis. However, the currently most used tool Wireshark is displaying the data as a table, making it difficult to get an overview and focus on the significant parts. Also, the process of loading large files into Wireshark takes time and has to be repeated each time the file is closed. We believe that this problem poses an optimal setting for a client-server infrastructure with a progressive visual analytics approach. The processing can be outsourced to the server while the client is progressively updated. In this paper we present NetCapVis, an web-based progressive visual analytics system where the user can upload PCAP files, set initial filters to reduce the data before uploading and then instantly interact with the data while the rest is progressively loaded into the visualizations.