Wyniki wyszukiwania - BazTech

1

Improvement of methods of motion compensation of dynamic objects moving in video stream of the videoconferencing system

Barannik V., Dvorsky M., Barannik V., Himenko V., Sorokun A.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2018

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T. 8, nr 4

48--51

EN

Videoconferencing gives us the opportunity to work and communicate in real time, as well as to use collective applications, interactive information exchange. Videoconferencing systems are one of the basic components of the organization of manegment, ensuring, the timeliness and necessary quality management of the implementation of objective control over the solution of the tasks. The quality of the image and the time of transmission of video information is unsatisfactory for the quality control of the troops. Considered ways to increase the efficiency of management and operational activities, due to methods of compensation of motion, using technology to reduce the volume of video data for quality improvement.

PL

Wideokonferencje dają możliwość pracy i komunikowania się w czasie rzeczywistym, a także korzystania ze zbiorowych aplikacji, interaktywnej wymiany informacji. Systemy wideokonferencyjne są jednym z podstawowych elementów organizacji zarządzania, zapewniając terminowość i niezbędne zarządzanie jakością w zakresie realizacji kontroli nad rozwiązaniem zadań. Jakość obrazu i czas transmisji informacji wideo jest niezadowalający dla kontroli jakości wojsk. Rozważono sposoby zwiększania efektywności zarządzania i działań operacyjnych, ze względu na metody kompensacji ruchu, z wykorzystaniem technologii zmniejszającej ilość danych wideo w celu poprawy jakości.

2

Algorithms for detecting disorders of the BLDC motor with direct control

Chodnicki M., Kordowski P., Nowakowski M., Kowaleczko G.

Journal of KONES

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2016

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Vol. 23, No. 4

49--54

EN

Unmanned aerial vehicles are used to observe objects from the air in both kind of users – military and civilian. During the flight, UAV constantly is changing its orientation. This is due to weather conditions and commands coming from the ground control station. It has directly influence to the quality of the video stream transmitted from the cameras to the GCS. That disturbed image is hard to effective analyse. In order to eliminate the interference, UAVs are equipped with stabilized gimbals. The most of gimbals designed in Air Force Institute of Technology are using BLDC motors. Some of these systems use encoders for determining the absolute angle of motor rotation. The smaller one, which is up to 200 g, is not provided with these sensors. This angle is calculated without any feedback from the system. It is calculated by the BLDC motor`s control signals. However, lack of feedback can provide unstable work of gimbal, if it will be pushed by any force from environment. During the flight, it is unacceptable to head optoelectronic stopped working steadily. Therefore, there is a need to develop algorithms for securing the proper operation of the system stability. These algorithms can be used in other systems using stepper or BLDC motors.

3

A wavelet-based vehicles detection algorithm

Pamuła W.

Zeszyty Naukowe. Transport / Politechnika Śląska

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2012

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z. 74

75-83

EN

The detection of vehicles, in video streams from road cameras, is generally performed by analyses of the occupancy of virtual detection fields defined in image frames. This principle of detection is sensitive to ambient light variations, vehicle shadows, and camera movement. The paper presents a method for detection of vehicles that uses transformed image frames. To facilitate detection each frame is converted into a vector of pixel values. Consecutive video vectors are transformed using one-dimensional DWT. Stopped vehicles are represented by stripes, whereas moving ones by checked patches. The width of a stripe indicates vehicle size, while the length shows how long the vehicle waited at the approach to the intersection.

PL

Wykrywanie pojazdów w strumieniu wideo z kamer drogowych oparte jest zwykle na analizie zajętości wirtualnych pól detekcji. Ten sposób wykrywania jest czuły na zmiany oświetlenia, cienie pojazdów i ruchy kamery. Artykuł przedstawia metodę wykrywania, która wykorzystuje transformaty klatek obrazów. W celu umożliwienia sprawnej analizy zawartość klatki zamieniana jest najpierw na wektor wartości pikseli. Kolejne wektory wideo są transformowane z użyciem jednowymiarowego, dyskretnego przekształcenia falkowego. Zatrzymane pojazdy są reprezentowane przez paski, a ruchome przez kratkowane placki. Szerokość paska wskazuje na rozmiar pojazdu, a długość określa, jak długo pojazd oczekiwał na wlocie skrzyżowania.

4

A method for QoS differentiation in DiffServ networks based on the long-term properties of a video stream

Omiotek Z.

Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica

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2012

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Vol. 12, no. 1

47--56

EN

This paper presents a method for adjusting the level of services offered by the network with quality of service differentiation for the long-term characteristics of a transmitted video stream. The Drop Precedence (DP) field located in the header of IP packet for this purpose was used.The DP field is set dynamically, based on the measurement of the long-term properties of a source video stream entering the network. The level of traffic perturbations present in a stream is expressed by the Hurst parameter, and then mapped to the size of a priority encoded in the DP field. By that means, an adaptive differentiation of the preferences of individual streams within the same AF PHB class of service is implemented, depending on the size of perturbations existing in the flow. The use of the long-term Hurst parameter, as a criterion of classification, makes the treatment of packets marked with a given priority value does the job well on a larger time scale.

5

Wavelet-Based Data Reduction for Detection of Moving Objects

Pamula W.

Machine Graphics and Vision

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2011

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Vol. 20, No. 1

27-40

EN

The detection of moving objects in video streams is generally performed by analysis of the differences between the modelled background and the current stream content, by matching object models, extracting and clustering the features of objects or else by using various filtering methods. Filtering is performed on the transformed contents of the video stream. Due to implementational constraints, mainly limited processing resources, solutions based on these principles of detection are sensitive to ambient light variations, objects shadows and camera movement. This paper presents a method for the detection of moving objects that uses a data reduction technique based on wavelets. Instead of the analysis of raw video data, wavelet coefficients of an appropriate scale are explored. In order to satisfy low processing requirements, an integer version of discrete wavelet transform is chosen for processing. To facilitate the detection, each frame is converted into a vector of pixel values. Consecutive video vectors are transformed using one-dimensional Discrete Wave Transform (DWT). The computed DWT coefficients make up a surface, which maps changes in their values over time. The surface is analysed to find clusters of values corresponding to moving objects. The checked patches represent moving objects. The width of a patch indicates the object size. Background details and illumination changes are represented by gradually changing patterns. Various examples demonstrate the potential of the method for practical applications.

6

The progressive transmission method based on the 2-D wavelet transform for a digital video signal

Murawski K.

Biuletyn Instytutu Automatyki i Robotyki

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2001

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R. 7, nr 15

15-25

EN

This paper presents a method of progressive digital transmission of a video stream, based on picture frame multi-resolution analysis.