TY - JOUR A1 - Hasche, Eberhard A1 - Karaschewski, Oliver A1 - Creutzburg, Reiner T1 - iPhone12 imagery in scene-referred computer graphics pipelines JF - Electronic Imaging N2 - With the release of the Apple iPhone 12 Pro Max in 2020, various features were integrated that make it attractive as a recording device for scene-related computer graphics pipelines. The captured Apple RAW images have a much higher dynamic range than the standard 8-bit images. Since a scene-based workflow naturally has an extended dynamic range (HDR), the Apple RAW recordings can be well integrated. To correctly integrate the iPhone 12 pro Apple RAW data into a scene-related workflow, two command-line software solutions, among others, are dcraw and rawtoaces. In this paper, we concentrate on dcraw. dcraw offers the possibility to export RAW images directly to ACES2065-1. Different images recorded under different lighting conditions are examined to determine which options for the dcraw development produce the best results. Images from five different lighting situations like D65, D60, D55, D50, and 2980K, are examined. The DNG files are developed using different methods within dcraw. The values of the recorded ColorChecker24 patches are compared to reference values derived from BabelColor [1] and ACES [2]. Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.3.MOBMU-350 SP - 350-1 EP - 350-14 PB - Society for Imaging Science and Technology ER - TY - JOUR A1 - Jaster, Daniel A1 - Creutzburg, Reiner A1 - Hasche, Eberhard T1 - A qualitative study of LiDAR technologies and their application areas JF - Electronic Imaging N2 - In this work, the most relevant 3D LiDAR technologies and their applications in 2022 were investigated. For this purpose, applications of LiDAR systems were classified into the typical application areas "3D modeling", "smart city", "robotics", "smart automotive" and "consumer goods". The investigation has shown that neither "mechanical" LiDAR technologies, nor so-called solid-state LiDAR technologies, nor "hybrid" LiDAR technologies can be evaluated as optimal for the typical application areas. In none of the application areas could all of the elaborated requirements be met. However, the "hybrid" LiDAR technologies such as sequential MEMS LiDAR technology and sequential flash LiDAR technology proved to be among the most suitable for most typical application areas. However, other technologies also tended to be suitable for individual typical application areas. Finally, it was found that several of the LiDAR technologies investigated are currently equally suitable for some typical application areas. To evaluate the suitability, concrete LiDAR systems - of different technologies and properties - were compared with the specific requirements of exemplary applications of an application area. The results of the investigation provide an orientation as to which LiDAR technology is promising for which application area. Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.3.MOBMU-368 VL - 35 SP - 368-1 EP - 368-15 PB - Society for Imaging Science and Technology ER - TY - JOUR A1 - Vishnevskaya, Valeria A1 - Schwarz, Klaus A1 - Creutzburg, Reiner T1 - Practical OSINT investigation - Similarity calculation using Reddit user profile data JF - Electronic Imaging N2 - This paper presents a practical Open Source Intelligence (OSINT) use case for user similarity measurements with the use of open profile data from the Reddit social network. This PoC work combines the open data from Reddit and the part of the state-of-the-art BERT model. Using the PRAW Python library, the project fetches comments and posts of users. Then these texts are converted into a feature vector - representation of all user posts and comments. The main idea here is to create a comparable user's pair similarity score based on their comments and posts. For example, if we fix one user and calculate scores of all mutual pairs with other users, we will produce a total order on the set of all mutual pairs with that user. This total order can be described as a degree of written similarity with this chosen user. A set of "similar" users for one particular user can be used to recommend to the user interesting for him people. The similarity score also has a "transitive property": if $user_1$ is "similar" to $user_2$ and $user_2$ is similar to $user_3$ then inner properties of our model guarantees that $user_1$ and $user_3$ are pretty "similar" too. In this way, this score can be used to cluster a set of users into sets of "similar" users. It could be used in some recommendation algorithms or tune already existing algorithms to consider a cluster's peculiarities. Also, we can extend our model and calculate feature vectors for subreddits. In that way, we can find similar to the user's subreddits and recommend them to him. Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.3.MOBMU-356 VL - 35 IS - 3 SP - 356-1 EP - 356-10 PB - Society for Imaging Science and Technology (IS&T) ER - TY - JOUR A1 - Skylar, Artem A1 - Schwarz, Klaus A1 - Creutzburg, Reiner T1 - Practical OSINT investigation in Twitter utilizing AI-based aggressiveness analysis JF - Electronic Imaging N2 - Open-source intelligence is gaining popularity due to the rapid development of social networks. There is more and more information in the public domain. One of the most popular social networks is Twitter. It was chosen to analyze the dependence of changes in the number of likes, reposts, quotes and retweets on the aggressiveness of the post text for a separate profile, as this information can be important not only for the owner of the channel in the social network, but also for other studies that in some way influence user accounts and their behavior in the social network. Furthermore, this work includes a detailed analysis and evaluation of the Tweety library capabilities and situations in which it can be effectively applied. Lastly, this work includes the creation and description of a compiled neural network whose purpose is to predict changes in the number of likes, reposts, quotes, and retweets from the aggressiveness of the post text for a separate profile. Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.3.MOBMU-355 VL - 35 IS - 3 SP - 355-1 EP - 355-15 PB - Society for Imaging Science and Technology (IS&T) ER - TY - JOUR A1 - Narasimhan, Pranesh Kumar A1 - Bhosale, Chinmay A1 - Pervez, Muhammad Hasban A1 - Naqvi, Najiba Zainab A1 - Ecevit, Mert Ilhan A1 - Schwarz, Klaus A1 - Creutzburg, Reiner T1 - Open-source Intelligence (OSINT) investigation in Facebook JF - Electronic Imaging N2 - Open Source Intelligence (OSINT) has come a long way, and it is still developing ideas, and lots of investigations are yet to happen in the near future. The main essential requirement for all the OSINT investigations is the information that is valuable data from a good source. This paper discusses various tools and methodologies related to Facebook data collection and analyzes part of the collected data. At the end of the paper, the reader will get a deep and clear insight into the available techniques, tools, and descriptions about tools that are present to scrape the data out of the Facebook platform and the types of investigations and analyses that the gathered data can do. Y1 - 2023 U6 - https://doi.org/10.2352/EI.2023.35.3.MOBMU-357 VL - 35 IS - 3 SP - 357-1 EP - 357-12 PB - Society for Imaging Science and Technology (IS&T) ER -