Diploma and Master Theses (authored and supervised):
"Visualization-Guided Classification of Carbonized Seeds from Early Human Civilizations";
Supervisor: E. Gröller, M. Waldner;
Institute of Visual Computing & Human-Centered Technology,
final examination: 2020-11-25.
Since the Neolithic Revolution approximately 10.000 years ago, crop plants are an important part of our food. Researchers of archeobotany try to ﬁnd and determine the species that humankind used already in the past. Most of the gathered samples are preserved due to carbonization, but the shape and inner structures are deformed because of this process. The amount of distortion is given by the temperature and the time they are heated. Normally, an expert is consulted to classify them. Since there are only a few experts in this ﬁeld, an automatic approach is requested. The result of this work is a software, which can load the Computed Tomography (CT) scans, segment and separate the seeds within the samples, calculate diﬀerent shape features as descriptors, and train a classiﬁer. To have an overview of how the seeds look like, diﬀerent volume visualizations are available to show selected samples or median seeds of each class. To validate the probabilities of the learner, additional visualizations are available, which show the inﬂuence of the extracted features on the classiﬁcation. A cross validation method with 1043 known samples results in a classiﬁcation accuracy of 85 %. The incorrectly classiﬁed samples of the ground truth are visualized to display the expert user where they are located regard to the extracted features and which results are especially inaccurate. It turned out, that the opportunity to export the features into a tabular ﬁletype and the visualization of the output probabilities of the classiﬁer for each species were particularly helpful for the domain experts.
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.