Download or read book Dynamic Switching State Systems for Visual Tracking written by Becker, Stefan and published by KIT Scientific Publishing. This book was released on 2020-12-02 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Proceedings of the 2022 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics Vision and Fusion Laboratory written by Beyerer, Jürgen and published by KIT Scientific Publishing. This book was released on 2023-07-05 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Proceedings of the 2020 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics Vision and Fusion Laboratory written by Beyerer, Jürgen and published by KIT Scientific Publishing. This book was released on 2021-06-22 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Proceedings of the 2021 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics Vision and Fusion Laboratory written by Beyerer, Jürgen and published by KIT Scientific Publishing. This book was released on 2022-07-05 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Probabilistic Parametric Curves for Sequence Modeling written by Hug, Ronny and published by KIT Scientific Publishing. This book was released on 2022-07-12 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Deep Learning based Vehicle Detection in Aerial Imagery written by Sommer, Lars Wilko and published by KIT Scientific Publishing. This book was released on 2022-02-09 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Multimodal Panoptic Segmentation of 3D Point Clouds written by Dürr, Fabian and published by KIT Scientific Publishing. This book was released on 2023-10-09 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Self learning Anomaly Detection in Industrial Production written by Meshram, Ankush and published by KIT Scientific Publishing. This book was released on 2023-06-19 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advances in Neural Information Processing Systems 13 written by Todd K. Leen and published by MIT Press. This book was released on 2001 with total page 1136 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Probabilistic Graphical Models for Computer Vision written by Qiang Ji and published by Academic Press. This book was released on 2019-11 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).

Download or read book Handbook of Dynamic Data Driven Applications Systems written by Erik P. Blasch and published by Springer Nature. This book was released on 2022-05-11 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies. Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in ten application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal: The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination. The Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms. Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions. In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide. Kelvin Droegemeier, Regents’ Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy We may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential. Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University

Download or read book Dynamic Data Assimilation written by Dinesh G. Harkut and published by BoD – Books on Demand. This book was released on 2020-10-28 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data assimilation is a process of fusing data with a model for the singular purpose of estimating unknown variables. It can be used, for example, to predict the evolution of the atmosphere at a given point and time. This book examines data assimilation methods including Kalman filtering, artificial intelligence, neural networks, machine learning, and cognitive computing.

Download or read book Machine Learning for Human Motion Analysis Theory and Practice written by Wang, Liang and published by IGI Global. This book was released on 2009-12-31 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book highlights the development of robust and effective vision-based motion understanding systems, addressing specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval"--Provided by publisher.

Download or read book Pattern Recognition written by Luc Van Gool and published by Springer. This book was released on 2003-06-30 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are proud to present the DAGM 2002 proceedings, which are the result of the e?orts of many people. First, there are the many authors, who have submitted so many excellent cont- butions. We received more than 140 papers, of which we could only accept about half in order not to overload the program. Only about one in seven submitted papers could be delivered as an oral presentation, for the same reason. But it needs to be said that almost all submissions were of a really high quality. This strong program could not have been put together without the support of the Program Committee. They took their responsibility most seriously and we are very grateful for their reviewing work, which certainly took more time than anticipated, given the larger than usual number of submissions. Our three invited speakers added a strong multidisciplinary component to the conference. Dr. Antonio Criminisi of Microsoft Research (Redmond, USA) dem- strated how computer vision can literally bring a new dimension to the app- ciation of art. Prof. Philippe Schyns (Dept. of Psychology, Univ. of Glasgow, UK) presented intriguing insights into the human perception of patterns, e.g., the role of scale. Complementary to this presentation, Prof. Manabu Tanifuji of the Brain Science Institute in Japan (Riken) discussed novel neurophysiological ?ndings on how the brain deals with the recognition of objects and their parts.

Download or read book Layered Tracker Switching for Visual Surveillance written by Ambrish Tyagi and published by . This book was released on 2008 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Surveillance and monitoring are two important applications of computer vision research. Many computer vision algorithms have been proposed to monitor both indoor and outdoor spaces using one or more visual sensors. Finding the location of objects (detection) in complex real-world scenes and following their position over time (tracking) are two principal tasks for these systems. In this thesis, we develop a computational framework for object tracking that layers multiple sources of information (such as position, velocity, and appearance) by automatically selecting the most appropriate tracking algorithm based on the given scene context. The proposed framework is independent of the choice of tracking algorithms used and is capable of automatically evaluating the spatial context based on object interactions in the scene. Our approach is to employ multiple trackers that have complimentary modes of success and failures. Also, these tracking algorithms range from simple to complex in terms of computation. We do not always need to deploy the most expensive tracker in all cases. Furthermore, we also propose a set of novel computer vision algorithms for tracking objects in both 2D and 3D spaces. These algorithms address various shortcomings of the existing tracking approaches such as occlusion reasoning, information fusion, model update strategies, execution speeds, etc. The proposed algorithms are deployed in the aforementioned layered tracker switching framework, resulting in robust and efficient paradigm for tracking objects in complex urban environments. First, we present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite (SPD) matrices that lie on a Riemannian manifold. This filtering approach is applied to the problem of object tracking by recursively estimating and updating the SPD covariance feature matrices representing objects in the scene. The online filtering process on the Riemannian manifold is used to recursively obtain the smoothed object location and the updated appearance model simultaneously. In addition, we also present a set of efficient optimizations to enhance covariance tracking algorithms that employ covariance matrices of image features to represent object appearance. The proposed optimization techniques improve the tracking accuracy while reducing execution times. Next we describe a 3D Kernel-based appearance tracking algorithm that combines information from multiple camera views to track an object directly in the 3D space. Its novelty lies in the proposed unified approach to 3D kernel tracking, that amounts to fusing the appearance features from all available camera sensors, as opposed to tracking the object appearance in the individual 2D views and fusing the results. The elegance of the method resides in its inherent ability to handle problems encountered by various 2D trackers, including scale selection, occlusion, view-dependence, and correspondence across different views. Finally, we demonstrate the applicability of the proposed tracker switching framework by developing practical systems for 2D and 3D object tracking. The layered tracking framework benefits by dynamically switching between simpler position and dynamics based algorithms and the advanced appearance based algorithms developed in this thesis. The net result is an improvement in tracking performance and efficiency.

Download or read book Creating Brain Like Intelligence written by Bernhard Sendhoff and published by Springer. This book was released on 2009-03-13 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: TheInternationalSymposiumCreatingBrain-LikeIntelligencewasheldinFeb- ary 2007 in Germany. The symposium brought together notable scientists from di?erent backgrounds and with di?erent expertise related to the emerging ?eld of brain-like intelligence. Our understanding of the principles behind brain-like intelligence is still limited. After all, we have had to acknowledge that after tremendous advances in areas like neural networks, computational and arti?cial intelligence (a ?eld that had just celebrated its 50 year anniversary) and fuzzy systems, we are still not able to mimic even the lower-level sensory capabilities of humans or animals. We asked what the biggest obstacles are and how we could gain ground toward a scienti?c understanding of the autonomy, ?exibility, and robustness of intelligent biological systems as they strive to survive. New principles are usually found at the interfaces between existing disciplines, and traditional boundaries between disciplines have to be broken down to see how complex systems become simple and how the puzzle can be assembled. During the symposium we could identify some recurring themes that p- vaded many of the talks and discussions. The triad of structure, dynamics and environment,theroleoftheenvironmentasanactivepartnerinshapingsystems, adaptivity on all scales (learning, development, evolution) and the amalga- tion of an internal and external world in brain-like intelligence rate high among them. Each of us is rooted in a certain community which we have to serve with the results of our research. Looking beyond our ?elds and working at the interfaces between established areas of research requires e?ort and an active process.