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Book Synopsis Feature-Based Probabilistic Data Association for Video-Based Multi-Object Tracking by : Grinberg, Michael
Download or read book Feature-Based Probabilistic Data Association for Video-Based Multi-Object Tracking written by Grinberg, Michael and published by KIT Scientific Publishing. This book was released on 2018-08-10 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This work proposes a feature-based probabilistic data association and tracking approach (FBPDATA) for multi-object tracking. FBPDATA is based on re-identification and tracking of individual video image points (feature points) and aims at solving the problems of partial, split (fragmented), bloated or missed detections, which are due to sensory or algorithmic restrictions, limited field of view of the sensors, as well as occlusion situations. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Book Synopsis Feature-Based Probabilistic Data Association for Video-Based Multi-Object Tracking by : Michael Grinberg
Download or read book Feature-Based Probabilistic Data Association for Video-Based Multi-Object Tracking written by Michael Grinberg and published by . This book was released on 2020-10-09 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work proposes a feature-based probabilistic data association and tracking approach (FBPDATA) for multi-object tracking. FBPDATA is based on re-identification and tracking of individual video image points (feature points) and aims at solving the problems of partial, split (fragmented), bloated or missed detections, which are due to sensory or algorithmic restrictions, limited field of view of the sensors, as well as occlusion situations. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
In the human quest for scientific knowledge, empirical evidence is collected by visual perception. Tracking with computer vision takes on the important role to reveal complex patterns of motion that exist in the world we live in. Multi-object tracking algorithms provide new information on how groups and individual group members move through three-dimensional space. They enable us to study in depth the relationships between individuals in moving groups. These may be interactions of pedestrians on a crowded sidewalk, living cells under a microscope, or bats emerging in large numbers from a cave. Being able to track pedestrians is important for urban planning; analysis of cell interactions supports research on biomaterial design; and the study of bat and bird flight can guide the engineering of aircraft. We were inspired by this multitude of applications to consider the crucial component needed to advance a single-object tracking system to a multi-object tracking system—data association. Data association in the most general sense is the process of matching information about newly observed objects with information that was previously observed about them. This information may be about their identities, positions, or trajectories. Algorithms for data association search for matches that optimize certain match criteria and are subject to physical conditions. They can therefore be formulated as solving a "constrained optimization problem"—the problem of optimizing an objective function of some variables in the presence of constraints on these variables. As such, data association methods have a strong mathematical grounding and are valuable general tools for computer vision researchers. This book serves as a tutorial on data association methods, intended for both students and experts in computer vision. We describe the basic research problems, review the current state of the art, and present some recently developed approaches. The book covers multi-object tracking in two and three dimensions. We consider two imaging scenarios involving either single cameras or multiple cameras with overlapping fields of view, and requiring across-time and across-view data association methods. In addition to methods that match new measurements to already established tracks, we describe methods that match trajectory segments, also called tracklets. The book presents a principled application of data association to solve two interesting tasks: first, analyzing the movements of groups of free-flying animals and second, reconstructing the movements of groups of pedestrians. We conclude by discussing exciting directions for future research.
Book Synopsis Data Association for Multi-Object Visual Tracking by : Margrit Betke
Download or read book Data Association for Multi-Object Visual Tracking written by Margrit Betke and published by Morgan & Claypool Publishers. This book was released on 2016-10-11 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the human quest for scientific knowledge, empirical evidence is collected by visual perception. Tracking with computer vision takes on the important role to reveal complex patterns of motion that exist in the world we live in. Multi-object tracking algorithms provide new information on how groups and individual group members move through three-dimensional space. They enable us to study in depth the relationships between individuals in moving groups. These may be interactions of pedestrians on a crowded sidewalk, living cells under a microscope, or bats emerging in large numbers from a cave. Being able to track pedestrians is important for urban planning; analysis of cell interactions supports research on biomaterial design; and the study of bat and bird flight can guide the engineering of aircraft. We were inspired by this multitude of applications to consider the crucial component needed to advance a single-object tracking system to a multi-object tracking system—data association. Data association in the most general sense is the process of matching information about newly observed objects with information that was previously observed about them. This information may be about their identities, positions, or trajectories. Algorithms for data association search for matches that optimize certain match criteria and are subject to physical conditions. They can therefore be formulated as solving a "constrained optimization problem"—the problem of optimizing an objective function of some variables in the presence of constraints on these variables. As such, data association methods have a strong mathematical grounding and are valuable general tools for computer vision researchers. This book serves as a tutorial on data association methods, intended for both students and experts in computer vision. We describe the basic research problems, review the current state of the art, and present some recently developed approaches. The book covers multi-object tracking in two and three dimensions. We consider two imaging scenarios involving either single cameras or multiple cameras with overlapping fields of view, and requiring across-time and across-view data association methods. In addition to methods that match new measurements to already established tracks, we describe methods that match trajectory segments, also called tracklets. The book presents a principled application of data association to solve two interesting tasks: first, analyzing the movements of groups of free-flying animals and second, reconstructing the movements of groups of pedestrians. We conclude by discussing exciting directions for future research.
The availability of video data is an opportunity and a challenge for law enforcement agencies. Face recognition methods can play a key role in the automated search for persons in the data. This work targets efficient representations of low-quality face sequences to enable fast and accurate face search. Novel concepts for multi-scale analysis, dataset augmentation, CNN loss function, and sequence description lead to improvements over state-of-the-art methods on surveillance video footage.
Book Synopsis Video-to-Video Face Recognition for Low-Quality Surveillance Data by : Herrmann, Christian
Download or read book Video-to-Video Face Recognition for Low-Quality Surveillance Data written by Herrmann, Christian and published by KIT Scientific Publishing. This book was released on 2018-08-03 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of video data is an opportunity and a challenge for law enforcement agencies. Face recognition methods can play a key role in the automated search for persons in the data. This work targets efficient representations of low-quality face sequences to enable fast and accurate face search. Novel concepts for multi-scale analysis, dataset augmentation, CNN loss function, and sequence description lead to improvements over state-of-the-art methods on surveillance video footage.
"This work proposes a Multibody Structure from Motion (MSfM) algorithm for moving object reconstruction that incorporates instance-aware semantic segmentation and multiple view geometry methods. The MSfM pipeline tracks two-dimensional object shapes on pixel level to determine object specific feature correspondences, in order to reconstruct 3D object shapes as well as 3D object motion trajectories" -- Publicaciones de Arquitectura y Arte.
Book Synopsis Image-Based 3D Reconstruction of Dynamic Objects Using Instance-Aware Multibody Structure from Motion by : Bullinger, Sebastian
Download or read book Image-Based 3D Reconstruction of Dynamic Objects Using Instance-Aware Multibody Structure from Motion written by Bullinger, Sebastian and published by KIT Scientific Publishing. This book was released on 2020-08-26 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This work proposes a Multibody Structure from Motion (MSfM) algorithm for moving object reconstruction that incorporates instance-aware semantic segmentation and multiple view geometry methods. The MSfM pipeline tracks two-dimensional object shapes on pixel level to determine object specific feature correspondences, in order to reconstruct 3D object shapes as well as 3D object motion trajectories" -- Publicaciones de Arquitectura y Arte.
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.
Book Synopsis Deep Learning based Vehicle Detection in Aerial Imagery by : Sommer, Lars Wilko
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.
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.
Book Synopsis Dynamic Switching State Systems for Visual Tracking by : Becker, Stefan
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.
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.
Book Synopsis Self-learning Anomaly Detection in Industrial Production by : Meshram, Ankush
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.
Book Synopsis Proceedings of the 2018 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory by : Beyerer, Jürgen
Download or read book Proceedings of the 2018 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 2019-07-12 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
In 2019 fand wieder der jährliche Workshop des Fraunhofer IOSB und des Lehrstuhls für Interaktive Echtzeitsysteme des Karlsruher Insitut für Technologie statt. Die Doktoranden beider Institutionen präsentierten den Fortschritt ihrer Forschung in den Themen Maschinelles Lernen, Machine Vision, Messtechnik, Netzwerksicherheit und Usage Control. Die Ideen dieses Workshops sind in diesem Buch gesammelt in der Form technischer Berichte. - In 2019 again, the annual joint workshop of the Fraunhofer IOSB and the Vision and Fusion Laboratory of the Karlsruhe Institute of Technology took place. 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 in the form of technical reports.
Book Synopsis Proceedings of the 2019 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory by : Beyerer, Jürgen
Download or read book Proceedings of the 2019 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 2020-10-23 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2019 fand wieder der jährliche Workshop des Fraunhofer IOSB und des Lehrstuhls für Interaktive Echtzeitsysteme des Karlsruher Insitut für Technologie statt. Die Doktoranden beider Institutionen präsentierten den Fortschritt ihrer Forschung in den Themen Maschinelles Lernen, Machine Vision, Messtechnik, Netzwerksicherheit und Usage Control. Die Ideen dieses Workshops sind in diesem Buch gesammelt in der Form technischer Berichte. - In 2019 again, the annual joint workshop of the Fraunhofer IOSB and the Vision and Fusion Laboratory of the Karlsruhe Institute of Technology took place. 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 in the form of technical reports.
