Vision-based Real-Time Aerial Object Localization and Tracking for UAV Sensing System

The paper focuses on the problem of vision-based obstacle detection and tracking for unmanned aerial vehicle navigation. A real-time object localization and tracking strategy from monocular image sequences is developed by effectively integrating the object detection and tracking into a dynamic Kalman model. At the detection stage, the object of interest is automatically detected and localized from a saliency map computed via the image background connectivity cue at each frame; at the tracking stage, a Kalman filter is employed to provide a coarse prediction of the object state, which is further refined via a local detector incorporating the saliency map and the temporal information between two consecutive frames. Compared to existing methods, the proposed approach does not require any manual initialization for tracking, runs much faster than the state-of-the-art trackers of its kind, and achieves competitive tracking performance on a large number of image sequences. Extensive experiments demonstrate the effectiveness and superior performance of the proposed approach.Comment: 8 pages, 7 figure

Contribution to Efficient Use of Narrowband Radio Channel

Předkládaná práce se soustředí na problematiku využívání úzkopásmového rádiového kanálu rádiovými modemy, které jsou určené pro průmyslové aplikace pozemní pohyblivé rádiové služby, specifikované v dominantní míře Evropským standardem ETSI EN 300 113. Tato rádiová zařízení se používají v kmitočtových pásmech od 30 MHz do 1 GHz s nejčastěji přidělovanou šířkou pásma 25 kHz a ve většině svých instalací jsou využívána ve fixních nebo mobilních bezdrátových sítích. Mezi typické oblasti použití patří zejména datová telemetrie, aplikace typu SCADA, nebo monitorování transportu strategických surovin. Za hlavní znaky popisovaného systému lze označit komunikační pokrytí značných vzdáleností, dané především vysokou výkonovou účinnosti datového přenosu a využívaní efektivních přístupových technik na rádiový kanál se semiduplexním komunikačním režimem. Striktní požadavky na elektromagnetickou kompatibilitu umožňují těmto zařízením využívat spektrum i v oblastech kmitočtově blízkým jiným komunikačním systémům bez nutnosti vkládání dodatečných ochranných frekvenčních pásem. Úzkopásmové rádiové komunikační systémy, v současnosti používají převážně exponenciální digitální modulace s konstantní modulační obálkou zejména z důvodů velice striktních omezení pro velikost výkonu vyzářeného do sousedního kanálu. Dosahují tak pouze kompromisních hodnot komunikační účinnosti. Úpravy limitů příslušných rádiových parametrů a rychlý rozvoj prostředků číslicového zpracování signálu v nedávné době, dnes umožňují ekonomicky přijatelné využití spektrálně efektivnějších modulačních technik i v těch oblastech, kde je prioritní využívání úzkých rádiových kanálů. Cílem předkládané disertační práce je proto výzkum postupů směřující ke sjednocení výhodných vlastností lineárních a nelineárních modulací v moderní konstrukci úzkopásmového rádiového modemu. Účelem tohoto výzkumu je efektivní a „ekologické“ využívání přidělené části frekvenčního spektra. Mezi hlavní dílčí problémy, jimiž se předkládaná práce zabývá, lze zařadit zejména tyto: Nyquistova modulační filtrace, navrhovaná s ohledem na minimalizaci nežádoucích elektromagnetických interferencí, efektivní číslicové algoritmy frekvenční demodulace a rychlé rámcové a symbolové synchronizace. Součástí práce je dále analýza navrhovaného řešení z pohledu celkové konstrukce programově definovaného rádiového modemu v rovině simulací při vyšetřování robustnosti datového přenosu rádiovým kanálem s bílým Gaussovským šumem nebo kanálem s únikem v důsledku mnohacestného šíření signálu. Závěr práce je pak zaměřen na prezentování výsledků praktické části projektu, v níž byly testovány, měřeny a analyzovány dvě prototypové konstrukce rádiového zařízení. Tato finální část práce obsahuje i praktická doporučení, vedoucí k vyššímu stupni využitelnosti spektrálně efektivnějších komunikačních režimů v oblasti budoucí generace úzkopásmových zařízení pozemní pohyblivé rádiové služby.he industrial narrowband land mobile radio (LMR) devices, as considered in this dissertation project, has been subject to European standard ETSI EN 300 113. The system operates on frequencies between 30 MHz and 1 GHz, with channel separations of up to 25 kHz, and is intended for private, fixed, or mobile, radio packet switching networks. Data telemetry, SCADA, maritime and police radio services; traffic monitoring; gas, water, and electricity producing factories are the typical system applications. Long distance coverage, high power efficiency, and efficient channel access techniques in half duplex operation are the primary advantages the system relays on. Very low level of adjacent channel power emissions and robust radio receiver architectures, with high dynamic range, enable for a system’s coexistence with various communication standards, without the additional guard band frequency intervals. On the other hand, the strict limitations of the referenced standard as well as the state of the technology, has hindered the increase in communication efficiency, with which the system has used its occupied bandwidth. New modifications and improvements are needed to the standard itself and to the up-to-date architectures of narrowband LMR devices, to make the utilization of more efficient modes of system operation practically realizable. The main objective of this dissertation thesis is therefore to find a practical way how to combine the favorable properties of the advanced nonlinear and linear digital modulation techniques in a single digital modem solution, in order to increase the efficiency of the narrowband radio channel usage allocated to the new generation of the industrial LMR devices. The main attention is given to the particular areas of digital modem design such as proposal of the new family of the Nyquist filters minimizing the adjacent channel interference, design and analysis of the efficient algorithms for frequency discrimination, fast frame and symbol

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Predicting Multiple Target Tracking Performance for Applications on Video Sequences

This dissertation presents a framework to predict the performance of multiple target tracking (MTT) techniques. The framework is based on the mathematical descriptors of point processes, the probability generating functional (p.g.fl). It is shown that conceptually the p.g.fls of MTT techniques can be interpreted as a transform that can be marginalized to an expression that encodes all the information regarding the likelihood model as well as the underlying assumptions present in a given tracking technique. In order to use this approach for tracker performance prediction in video sequences, a framework that combines video quality assessment concepts and the marginalized transform is introduced. The multiple hypothesis tracker (MHT), Joint Probabilistic Data Association (JPDA), Markov Chain Monte Carlo (MCMC) data association, and the Probability Hypothesis Density filter (PHD) are used as a test cases. We introduce their transforms and perform a numerical comparison to predict their performance under identical conditions. We also introduce the concepts that present the base for estimation in general and for applications in computer vision

Efficient approximations of the multi-sensor labelled multi-Bernoulli filter

In this paper, we propose two efficient, approximate formulations of the multi-sensor labelled multi-Bernoulli (LMB) filter, which both allow the sensors' measurement updates to be computed in parallel. Our first filter is based on the direct mathematical manipulation of the multi-sensor, multi-object Bayes filter's posterior distribution. Unfortunately, it requires the division of probability distributions and its extension beyond linear Gaussian applications is not obvious. Our second filter is based on covariance intersection and it approximates the multi-sensor, multi-object Bayes filter's posterior distribution using the geometric mean of each sensor's measurement-updated distribution. This filter can be used for distributed fusion under non-linear conditions; however, it is not as accurate as our first filter. In both cases, we approximate the LMB filter's measurement update using an existing loopy belief propagation algorithm, which we adapt to account for object existence. Both filters have a constant complexity in the number of sensors, and linear complexity in both number of measurements and objects. This is an improvement on an iterated-corrector LMB filter, which has linear complexity in the number of sensors. We evaluate both filters' performances on simulated data and the results indicate that the filters are accurate

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world