Dynamic Switching State Systems for Visual Tracking

Dynamic Switching State Systems for Visual Tracking PDF Author: Becker, Stefan
Publisher: KIT Scientific Publishing
ISBN: 3731510383
Category : Computers
Languages : en
Pages : 228

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Book Description
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.

Dynamic Switching State Systems for Visual Tracking

Dynamic Switching State Systems for Visual Tracking PDF Author: Becker, Stefan
Publisher: KIT Scientific Publishing
ISBN: 3731510383
Category : Computers
Languages : en
Pages : 228

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Book Description
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.

Proceedings of the 2022 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

Proceedings of the 2022 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory PDF Author: Beyerer, Jürgen
Publisher: KIT Scientific Publishing
ISBN: 3731513048
Category :
Languages : en
Pages : 140

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Book Description
In August 2022, Fraunhofer IOSB and IES of KIT held a joint workshop in a Schwarzwaldhaus near Triberg. Doctoral students presented research reports and discussed various topics like computer vision, optical metrology, network security, usage control, and machine learning. This book compiles the workshop's results and ideas, offering a comprehensive overview of the research program of IES and Fraunhofer IOSB.

Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory PDF Author: Beyerer, Jürgen
Publisher: KIT Scientific Publishing
ISBN: 373151091X
Category : Computers
Languages : en
Pages : 192

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Book Description
In 2020 fand der jährliche Workshop des Faunhofer IOSB und the Lehrstuhls für interaktive Echtzeitsysteme statt. Vom 27. bis zum 31. Juli trugen die Doktorranden der beiden Institute über den Stand ihrer Forschung vor in Themen wie KI, maschinellen Lernen, computer vision, usage control, Metrologie vor. Die Ergebnisse dieser Vorträge sind in diesem Band als technische Berichte gesammelt. - In 2020, the annual joint workshop of the Fraunhofer IOSB and the Vision and Fusion Laboratory of the KIT was hosted at the IOSB in Karlsruhe. For a week from the 27th to the 31st July the doctoral students of both institutions presented extensive reports on the status of their research and discussed topics ranging from computer vision and optical metrology to network security, usage control and machine learning. The results and ideas presented at the workshop are collected in this book.

Proceedings of the 2021 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

Proceedings of the 2021 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory PDF Author: Beyerer, Jürgen
Publisher: KIT Scientific Publishing
ISBN: 3731511711
Category : Computers
Languages : en
Pages : 242

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Book Description
2021, the annual joint workshop of the Fraunhofer IOSB and KIT IES was hosted at the IOSB in Karlsruhe. For a week from the 2nd to the 6th July the doctoral students extensive reports on the status of their research. The results and ideas presented at the workshop are collected in this book in the form of detailed technical reports.

Probabilistic Parametric Curves for Sequence Modeling

Probabilistic Parametric Curves for Sequence Modeling PDF Author: Hug, Ronny
Publisher: KIT Scientific Publishing
ISBN: 3731511983
Category : Mathematics
Languages : en
Pages : 224

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Book Description
This work proposes a probabilistic extension to Bézier curves as a basis for effectively modeling stochastic processes with a bounded index set. The proposed stochastic process model is based on Mixture Density Networks and Bézier curves with Gaussian random variables as control points. A key advantage of this model is given by the ability to generate multi-mode predictions in a single inference step, thus avoiding the need for Monte Carlo simulation.

Deep Learning based Vehicle Detection in Aerial Imagery

Deep Learning based Vehicle Detection in Aerial Imagery PDF Author: Sommer, Lars Wilko
Publisher: KIT Scientific Publishing
ISBN: 3731511134
Category : Computers
Languages : en
Pages : 276

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Book Description
This book proposes a novel deep learning based detection method, focusing on vehicle detection in aerial imagery recorded in top view. The base detection framework is extended by two novel components to improve the detection accuracy by enhancing the contextual and semantical content of the employed feature representation. To reduce the inference time, a lightweight CNN architecture is proposed as base architecture and a novel module that restricts the search area is introduced.

Multimodal Panoptic Segmentation of 3D Point Clouds

Multimodal Panoptic Segmentation of 3D Point Clouds PDF Author: Dürr, Fabian
Publisher: KIT Scientific Publishing
ISBN: 3731513145
Category :
Languages : en
Pages : 248

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Book Description
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.

Self-learning Anomaly Detection in Industrial Production

Self-learning Anomaly Detection in Industrial Production PDF Author: Meshram, Ankush
Publisher: KIT Scientific Publishing
ISBN: 3731512572
Category :
Languages : en
Pages : 224

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Book Description
Configuring an anomaly-based Network Intrusion Detection System for cybersecurity of an industrial system in the absence of information on networking infrastructure and programmed deterministic industrial process is challenging. Within the research work, different self-learning frameworks to analyze passively captured network traces from PROFINET-based industrial system for protocol-based and process behavior-based anomaly detection are developed, and evaluated on a real-world industrial system.

Advances in Neural Information Processing Systems 13

Advances in Neural Information Processing Systems 13 PDF Author: Todd K. Leen
Publisher: MIT Press
ISBN: 9780262122412
Category : Artificial intelligence
Languages : en
Pages : 1136

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Book Description
The proceedings of the 2000 Neural Information Processing Systems (NIPS) Conference.The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented at the 2000 conference.

Probabilistic Graphical Models for Computer Vision

Probabilistic Graphical Models for Computer Vision PDF Author: Qiang Ji
Publisher: Academic Press
ISBN: 012803467X
Category :
Languages : en
Pages : 294

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Book Description
Probabilistic Graphical Models for Computer Vision introduces probabilistic graphical models (PGMs) for computer vision problems and teaches how to develop the PGM model from training data. This book discusses PGMs and their significance in the context of solving computer vision problems, giving the basic concepts, definitions and properties. It also provides a comprehensive introduction to well-established theories for different types of PGMs, including both directed and undirected PGMs, such as Bayesian Networks, Markov Networks and their variants. Discusses PGM theories and techniques with computer vision examples Focuses on well-established PGM theories that are accompanied by corresponding pseudocode for computer vision Includes an extensive list of references, online resources and a list of publicly available and commercial software Covers computer vision tasks, including feature extraction and image segmentation, object and facial recognition, human activity recognition, object tracking and 3D reconstruction