Real-Time Salient Closed Boundary Tracking via Line Segments Perceptual Grouping

This paper presents a novel real-time method for tracking salient closed boundaries from video image sequences. This method operates on a set of straight line segments that are produced by line detection. The tracking scheme is coherently integrated into a perceptual grouping framework in which the visual tracking problem is tackled by identifying a subset of these line segments and connecting them sequentially to form a closed boundary with the largest saliency and a certain similarity to the previous one. Specifically, we define a new tracking criterion which combines a grouping cost and an area similarity constraint. The proposed criterion makes the resulting boundary tracking more robust to local minima. To achieve real-time tracking performance, we use Delaunay Triangulation to build a graph model with the detected line segments and then reduce the tracking problem to finding the optimal cycle in this graph. This is solved by our newly proposed closed boundary candidates searching algorithm called "Bidirectional Shortest Path (BDSP)". The efficiency and robustness of the proposed method are tested on real video sequences as well as during a robot arm pouring experiment.Comment: 7 pages, 8 figures, The 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017) submission ID 103

A review on technologies for localisation and navigation in autonomous railway maintenance systems

Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruption and unsafe operations. The deployment of robotic and autonomous systems was proposed to conduct these maintenance tasks with higher accuracy and reliability. In order for these systems to be capable of detecting rail flaws along millions of mileages they must register their location with higher accuracy. A prerequisite of an autonomous vehicle is its possessing a high degree of accuracy in terms of its positional awareness. This paper first reviews the importance and demands of preventive maintenance in railway networks and the related techniques. Furthermore, this paper investigates the strategies, techniques, architecture, and references used by different systems to resolve the location along the railway network. Additionally, this paper discusses the advantages and applicability of on-board-based and infrastructure-based sensing, respectively. Finally, this paper analyses the uncertainties which contribute to a vehicle’s position error and influence on positioning accuracy and reliability with corresponding technique solutions. This study therefore provides an overall direction for the development of further autonomous track-based system designs and methods to deal with the challenges faced in the railway network.European Union’s Horizon 2020 research and innovation programme. Shift2Rail Joint Undertaking (JU): 88157

Probabilistic modeling and inference for sequential space-varying blur identification

International audienceThe identification of parameters of spatially variant blurs given a clean image and its blurry noisy version is a challenging inverse problem of interest in many application fields, such as biological microscopy and astronomical imaging. In this paper, we consider a parametric model of the blur and introduce an 1D state-space model to describe the statistical dependence among the neighboring kernels. We apply a Bayesian approach to estimate the posterior distribution of the kernel parameters given the available data. Since this posterior is intractable for most realistic models, we propose to approximate it through a sequential Monte Carlo approach by processing all data in a sequential and efficient manner. Additionally, we propose a new sampling method to alleviate the particle degeneracy problem, which is present in approximate Bayesian filtering, particularly in challenging concentrated posterior distributions. The considered method allows us to process sequentially image patches at a reasonable computational and memory costs. Moreover, the probabilistic approach we adopt in this paper provides uncertainty quantification which is useful for image restoration. The practical experimental results illustrate the improved estimation performance of our novel approach, demonstrating also the benefits of exploiting the spatial structure the parametric blurs in the considered models

Sistem Pemandu Pengemudi Berbasis Kamera Embeded

Keamanan dan kenyamanan berkendara merupakan salah satu aspek penting yang harus diperhatikan oleh industri otomotif. Sebuah sistem yang mampu memberikan peringatan dini pada pengemudi akan membantu mencegah terjadinya kecelakaan. Sistem pemandu pengemudi (Driver assistance system) merupakan sistem yang dikembangkan untuk menyediakan fungsi tersebut. Sistem pemandu pengemudi berbasis kamera merupakan sistem yang berkembang cukup pesat, seiring dengan perkembangan teknologi di bidang teknik pengolahan citra digital dan sistem komputer. Penelitian ini bertujuan untuk mengembangkan sistem pemandu pengemudi berbasis kamera yang mampu mendeteksi kelelahan dan konsentrasi/pandangan mata pengemudi, rambu-rambu lalu lintas, dan marka jalan, serta objek atau kendaraan yang berada di depan. Pada peneltian di tahun pertama, dikembangkan sistem pendeteksi kelelahan pengemudi menggunakan kamera embeded yang dipasang di ruang kemudi kendaraan. Sebuah sistem komputer embeded digunakan sebagai pengolah utama dalam proses pendeteksian berbasis kamera tersebut. Dengan menggunakan sistem embeded ini, implementasi sistem di kendaraan dapat dilakukan dengan mudah dan murah

Analysis Of Cross-Layer Optimization Of Facial Recognition In Automated Video Surveillance

Interest in automated video surveillance systems has grown dramatically and with that so too has research on the topic. Recent approaches have begun addressing the issues of scalability and cost. One method aimed to utilize cross-layer information for adjusting bandwidth allocated to each video source. Work on this topic focused on using distortion and accuracy for face detection as an adjustment metric, utilizing older, less efficient codecs. The framework was shown to increase accuracy in face detection by interpreting dynamic network conditions in order to manage application rates and transmission opportunities for video sources with the added benefit of reducing overall network load and power consumption. In this thesis, we analyze the effectiveness of an accuracy-based cross-layer bandwidth allocation solution when used in conjunction with facial recognition tasks. In addition, we consider the effectiveness of the optimization when combined with H.264. We perform analysis of the Honda/UCSD face database to characterize the relationship between facial recognition accuracy and bitrate. Utilizing OPNET, we develop a realistic automated video surveillance system that includes a full video streaming and facial recognition implementation. We conduct extensive experimentation that examines the effectiveness of the framework to maximize facial recognition accuracy while utilizing the H.264 video codec. In addition, network load and power consumption characteristics are examined to observe what benefits may exist when using a codec that maintains video quality at lower bitrates more effectively than previously tested codecs. We propose two enhancements to the accuracy-based cross-layer bandwidth optimization solution. In the first enhancement we evaluate the effectiveness of placing a cap on bandwidth to reduce excessive bandwidth usage. The second enhancement explores the effectiveness of distributing computer vision tasks to smart cameras in order to reduce network load. The results show that cross-layer optimization of facial recognition is effective in reducing load and power consumption in automated video surveillance networks. Furthermore, the analysis shows that the solution is effective when using H.264. Additionally, the proposed enhancements demonstrate further reductions to network load and power consumption while also maintaining facial recognition accuracy across larger network sizes

Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction

Meyer zu Borgsen S. Nonverbal Communication During Human-Robot Object Handover. Improving Predictability of Humanoid Robots by Gaze and Gestures in Close Interaction. Bielefeld: Universität Bielefeld; 2020.This doctoral thesis investigates the influence of nonverbal communication on human-robot object handover. Handing objects to one another is an everyday activity where two individuals cooperatively interact. Such close interactions incorporate a lot of nonverbal communication in order to create alignment in space and time. Understanding and transferring communication cues to robots becomes more and more important as e.g. service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot interaction. A lot of work in this field of research focuses on speed, accuracy, and predictability of the robot’s movement during object handover. Still, robots need to be enabled to closely interact with naive users and not only experts. In this work I present how nonverbal communication can be implemented in robots to facilitate smooth handovers. I conducted a study on people with different levels of experience exchanging objects with a humanoid robot. It became clear that especially users with only little experience in regard to interaction with robots rely heavily on the communication cues they are used to on the basis of former interactions with humans. I added different gestures with the second arm, not directly involved in the transfer, to analyze the influence on synchronization, predictability, and human acceptance. Handing an object has a special movement trajectory itself which has not only the purpose of bringing the object or hand to the position of exchange but also of socially signalizing the intention to exchange an object. Another common type of nonverbal communication is gaze. It allows guessing the focus of attention of an interaction partner and thus helps to predict the next action. In order to evaluate handover interaction performance between human and robot, I applied the developed concepts to the humanoid robot Meka M1. By adding the humanoid robot head named Floka Head to the system, I created the Floka humanoid, to implement gaze strategies that aim to increase predictability and user comfort. This thesis contributes to the field of human-robot object handover by presenting study outcomes and concepts along with an implementation of improved software modules resulting in a fully functional object handing humanoid robot from perception and prediction capabilities to behaviors enhanced and improved by features of nonverbal communication

Understanding and designing for control in camera operation

Kameraleute nutzen traditionell gezielt Hilfsmittel um kontrollierte Kamerabewegungen zu ermöglichen. Der technische Fortschritt hat hierbei unlängst zum Entstehen neuer Werkzeugen wie Gimbals, Drohnen oder Robotern beigetragen. Dabei wurden durch eine Kombination von Motorisierung, Computer-Vision und Machine-Learning auch neue Interaktionstechniken eingeführt. Neben dem etablierten achsenbasierten Stil wurde nun auch ein inhaltsbasierter Interaktionsstil ermöglicht. Einerseits vereinfachte dieser die Arbeit, andererseits aber folgten dieser (Teil-)Automatisierung auch unerwünschte Nebeneffekte. Grundsätzlich wollen sich Kameraleute während der Kamerabewegung kontinuierlich in Kontrolle und am Ende als Autoren der Aufnahmen fühlen. Während Automatisierung hierbei Experten unterstützen und Anfänger befähigen kann, führt sie unweigerlich auch zu einem gewissen Verlust an gewünschter Kontrolle. Wenn wir Kamerabewegung mit neuen Werkzeugen unterstützen wollen, stellt sich uns daher die Frage: Wie sollten wir diese Werkzeuge gestalten damit sie, trotz fortschreitender Automatisierung ein Gefühl von Kontrolle vermitteln? In der Vergangenheit wurde Kamerakontrolle bereits eingehend erforscht, allerdings vermehrt im virtuellen Raum. Die Anwendung inhaltsbasierter Kontrolle im physikalischen Raum trifft jedoch auf weniger erforschte domänenspezifische Herausforderungen welche gleichzeitig auch neue Gestaltungsmöglichkeiten eröffnen. Um dabei auf Nutzerbedürfnisse einzugehen, müssen sich Schnittstellen zum Beispiel an diese Einschränkungen anpassen können und ein Zusammenspiel mit bestehenden Praktiken erlauben. Bisherige Forschung fokussierte sich oftmals auf ein technisches Verständnis von Kamerafahrten, was sich auch in der Schnittstellengestaltung niederschlug. Im Gegensatz dazu trägt diese Arbeit zu einem besseren Verständnis der Motive und Praktiken von Kameraleuten bei und bildet eine Grundlage zur Forschung und Gestaltung von Nutzerschnittstellen. Diese Arbeit präsentiert dazu konkret drei Beiträge: Zuerst beschreiben wir ethnographische Studien über Experten und deren Praktiken. Sie zeigen vor allem die Herausforderungen von Automatisierung bei Kreativaufgaben auf (Assistenz vs. Kontrollgefühl). Zweitens, stellen wir ein Prototyping-Toolkit vor, dass für den Einsatz im Feld geeignet ist. Das Toolkit stellt Software für eine Replikation quelloffen bereit und erleichtert somit die Exploration von Designprototypen. Um Fragen zu deren Gestaltung besser beantworten zu können, stellen wir ebenfalls ein Evaluations-Framework vor, das vor allem Kontrollqualität und -gefühl bestimmt. Darin erweitern wir etablierte Ansätze um eine neurowissenschaftliche Methodik, um Daten explizit wie implizit erheben zu können. Drittens, präsentieren wir Designs und deren Evaluation aufbauend auf unserem Toolkit und Framework. Die Alternativen untersuchen Kontrolle bei verschiedenen Automatisierungsgraden und inhaltsbasierten Interaktionen. Auftretende Verdeckung durch graphische Elemente, wurde dabei durch visuelle Reduzierung und Mid-Air Gesten kompensiert. Unsere Studien implizieren hohe Grade an Kontrollqualität und -gefühl bei unseren Ansätzen, die zudem kreatives Arbeiten und bestehende Praktiken unterstützen.Cinematographers often use supportive tools to craft desired camera moves. Recent technological advances added new tools to the palette such as gimbals, drones or robots. The combination of motor-driven actuation, computer vision and machine learning in such systems also rendered new interaction techniques possible. In particular, a content-based interaction style was introduced in addition to the established axis-based style. On the one hand, content-based cocreation between humans and automated systems made it easier to reach high level goals. On the other hand however, the increased use of automation also introduced negative side effects. Creatives usually want to feel in control during executing the camera motion and in the end as the authors of the recorded shots. While automation can assist experts or enable novices, it unfortunately also takes away desired control from operators. Thus, if we want to support cinematographers with new tools and interaction techniques the following question arises: How should we design interfaces for camera motion control that, despite being increasingly automated, provide cinematographers with an experience of control? Camera control has been studied for decades, especially in virtual environments. Applying content-based interaction to physical environments opens up new design opportunities but also faces, less researched, domain-specific challenges. To suit the needs of cinematographers, designs need to be crafted with care. In particular, they must adapt to constraints of recordings on location. This makes an interplay with established practices essential. Previous work has mainly focused on a technology-centered understanding of camera travel which consequently influenced the design of camera control systems. In contrast, this thesis, contributes to the understanding of the motives of cinematographers, how they operate on set and provides a user-centered foundation informing cinematography specific research and design. The contribution of this thesis is threefold: First, we present ethnographic studies on expert users and their shooting practices on location. These studies highlight the challenges of introducing automation to a creative task (assistance vs feeling in control). Second, we report on a domain specific prototyping toolkit for in-situ deployment. The toolkit provides open source software for low cost replication enabling the exploration of design alternatives. To better inform design decisions, we further introduce an evaluation framework for estimating the resulting quality and sense of control. By extending established methodologies with a recent neuroscientific technique, it provides data on explicit as well as implicit levels and is designed to be applicable to other domains of HCI. Third, we present evaluations of designs based on our toolkit and framework. We explored a dynamic interplay of manual control with various degrees of automation. Further, we examined different content-based interaction styles. Here, occlusion due to graphical elements was found and addressed by exploring visual reduction strategies and mid-air gestures. Our studies demonstrate that high degrees of quality and sense of control are achievable with our tools that also support creativity and established practices

Understanding and designing for control in camera operation

Kameraleute nutzen traditionell gezielt Hilfsmittel um kontrollierte Kamerabewegungen zu ermöglichen. Der technische Fortschritt hat hierbei unlängst zum Entstehen neuer Werkzeugen wie Gimbals, Drohnen oder Robotern beigetragen. Dabei wurden durch eine Kombination von Motorisierung, Computer-Vision und Machine-Learning auch neue Interaktionstechniken eingeführt. Neben dem etablierten achsenbasierten Stil wurde nun auch ein inhaltsbasierter Interaktionsstil ermöglicht. Einerseits vereinfachte dieser die Arbeit, andererseits aber folgten dieser (Teil-)Automatisierung auch unerwünschte Nebeneffekte. Grundsätzlich wollen sich Kameraleute während der Kamerabewegung kontinuierlich in Kontrolle und am Ende als Autoren der Aufnahmen fühlen. Während Automatisierung hierbei Experten unterstützen und Anfänger befähigen kann, führt sie unweigerlich auch zu einem gewissen Verlust an gewünschter Kontrolle. Wenn wir Kamerabewegung mit neuen Werkzeugen unterstützen wollen, stellt sich uns daher die Frage: Wie sollten wir diese Werkzeuge gestalten damit sie, trotz fortschreitender Automatisierung ein Gefühl von Kontrolle vermitteln? In der Vergangenheit wurde Kamerakontrolle bereits eingehend erforscht, allerdings vermehrt im virtuellen Raum. Die Anwendung inhaltsbasierter Kontrolle im physikalischen Raum trifft jedoch auf weniger erforschte domänenspezifische Herausforderungen welche gleichzeitig auch neue Gestaltungsmöglichkeiten eröffnen. Um dabei auf Nutzerbedürfnisse einzugehen, müssen sich Schnittstellen zum Beispiel an diese Einschränkungen anpassen können und ein Zusammenspiel mit bestehenden Praktiken erlauben. Bisherige Forschung fokussierte sich oftmals auf ein technisches Verständnis von Kamerafahrten, was sich auch in der Schnittstellengestaltung niederschlug. Im Gegensatz dazu trägt diese Arbeit zu einem besseren Verständnis der Motive und Praktiken von Kameraleuten bei und bildet eine Grundlage zur Forschung und Gestaltung von Nutzerschnittstellen. Diese Arbeit präsentiert dazu konkret drei Beiträge: Zuerst beschreiben wir ethnographische Studien über Experten und deren Praktiken. Sie zeigen vor allem die Herausforderungen von Automatisierung bei Kreativaufgaben auf (Assistenz vs. Kontrollgefühl). Zweitens, stellen wir ein Prototyping-Toolkit vor, dass für den Einsatz im Feld geeignet ist. Das Toolkit stellt Software für eine Replikation quelloffen bereit und erleichtert somit die Exploration von Designprototypen. Um Fragen zu deren Gestaltung besser beantworten zu können, stellen wir ebenfalls ein Evaluations-Framework vor, das vor allem Kontrollqualität und -gefühl bestimmt. Darin erweitern wir etablierte Ansätze um eine neurowissenschaftliche Methodik, um Daten explizit wie implizit erheben zu können. Drittens, präsentieren wir Designs und deren Evaluation aufbauend auf unserem Toolkit und Framework. Die Alternativen untersuchen Kontrolle bei verschiedenen Automatisierungsgraden und inhaltsbasierten Interaktionen. Auftretende Verdeckung durch graphische Elemente, wurde dabei durch visuelle Reduzierung und Mid-Air Gesten kompensiert. Unsere Studien implizieren hohe Grade an Kontrollqualität und -gefühl bei unseren Ansätzen, die zudem kreatives Arbeiten und bestehende Praktiken unterstützen.Cinematographers often use supportive tools to craft desired camera moves. Recent technological advances added new tools to the palette such as gimbals, drones or robots. The combination of motor-driven actuation, computer vision and machine learning in such systems also rendered new interaction techniques possible. In particular, a content-based interaction style was introduced in addition to the established axis-based style. On the one hand, content-based cocreation between humans and automated systems made it easier to reach high level goals. On the other hand however, the increased use of automation also introduced negative side effects. Creatives usually want to feel in control during executing the camera motion and in the end as the authors of the recorded shots. While automation can assist experts or enable novices, it unfortunately also takes away desired control from operators. Thus, if we want to support cinematographers with new tools and interaction techniques the following question arises: How should we design interfaces for camera motion control that, despite being increasingly automated, provide cinematographers with an experience of control? Camera control has been studied for decades, especially in virtual environments. Applying content-based interaction to physical environments opens up new design opportunities but also faces, less researched, domain-specific challenges. To suit the needs of cinematographers, designs need to be crafted with care. In particular, they must adapt to constraints of recordings on location. This makes an interplay with established practices essential. Previous work has mainly focused on a technology-centered understanding of camera travel which consequently influenced the design of camera control systems. In contrast, this thesis, contributes to the understanding of the motives of cinematographers, how they operate on set and provides a user-centered foundation informing cinematography specific research and design. The contribution of this thesis is threefold: First, we present ethnographic studies on expert users and their shooting practices on location. These studies highlight the challenges of introducing automation to a creative task (assistance vs feeling in control). Second, we report on a domain specific prototyping toolkit for in-situ deployment. The toolkit provides open source software for low cost replication enabling the exploration of design alternatives. To better inform design decisions, we further introduce an evaluation framework for estimating the resulting quality and sense of control. By extending established methodologies with a recent neuroscientific technique, it provides data on explicit as well as implicit levels and is designed to be applicable to other domains of HCI. Third, we present evaluations of designs based on our toolkit and framework. We explored a dynamic interplay of manual control with various degrees of automation. Further, we examined different content-based interaction styles. Here, occlusion due to graphical elements was found and addressed by exploring visual reduction strategies and mid-air gestures. Our studies demonstrate that high degrees of quality and sense of control are achievable with our tools that also support creativity and established practices

Technology transfer practices and strategies: Issues for Nigerian construction organisations and for research

Technology transfer is increasingly being seen as an important issue for economic development and growth. Arguably, this is why developed and especially developing countries are very keen on technology transfer. However, there are those that contend that organisations in the Nigerian construction industry are not as engaged in technology transfer as many would like, and that potential benefits of doing so are not realized. In the same vein, the challenges that confront construction organisations in Nigeria in terms of technology transfer have received very little empirical studies. This paper, therefore, presents a thorough review of literature on strategic issues and choices that Nigerian construction organisations face in grappling with technology transfer, together with associated challenges. Consideration is also given to what technology transfer actually means to such organisations, and how this is viewed in line with other terms such as innovation. The paper argues and concludes that the challenges that confront construction organisations in Nigeria are multifaceted and likely to impact on their strategic choices. In the same vein, it is also argued that these have implications for researchers attempting to investigate technology transfer practices and strategies in construction organisations in Nigeria in terms of their choice of research strategy and design