Dynamic Switching State Systems For Visual Tracking
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Dynamic Switching State Systems for Visual Tracking
Author: Becker, Stefan
language: en
Publisher: KIT Scientific Publishing
Release Date: 2020-12-02
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.
Distributed Planning for Self-Organizing Production Systems
Author: Pfrommer, Julius
language: en
Publisher: KIT Scientific Publishing
Release Date: 2024-06-04
In dieser Arbeit wird ein Ansatz entwickelt, um eine automatische Anpassung des Verhaltens von Produktionsanlagen an wechselnde Aufträge und Rahmenbedingungen zu erreichen. Dabei kommt das Prinzip der Selbstorganisation durch verteilte Planung zum Einsatz. - Most production processes are rigid not only by way of the physical layout of machines and their integration, but also by the custom programming of the control logic for the integration of components to a production systems. Changes are time- and resource-expensive. This makes the production of small lot sizes of customized products economically challenging. This work develops solutions for the automated adaptation of production systems based on self-organisation and distributed planning.
Multimodal Panoptic Segmentation of 3D Point Clouds
Author: Dürr, Fabian
language: en
Publisher: KIT Scientific Publishing
Release Date: 2023-10-09
The understanding and interpretation of complex 3D environments is a key challenge of autonomous driving. Lidar sensors and their recorded point clouds are particularly interesting for this challenge since they provide accurate 3D information about the environment. This work presents a multimodal approach based on deep learning for panoptic segmentation of 3D point clouds. It builds upon and combines the three key aspects multi view architecture, temporal feature fusion, and deep sensor fusion.