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    Wyświetlanie 1-4 z 4
    Tytuł:
    Video key frame detection based on the restricted Boltzmann machine
    Autorzy:
    Knop, M.
    Kapuściński, T.
    Mleczko, W. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/122435.pdf
    Data publikacji:
    2015
    Wydawca:
    Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
    Tematy:
    Restricted Boltzmann Machine
    key frame detection
    video compression
    Opis:
    In this paper we present a new method for key frame detection. Our approach is based on a well-known algorithm of the Restricted Boltzmann Machine (RBM), which is a pivotal step in our method. The frames are compared to the RBM matcher, which allows one to search for key frame in the video sequence. The Restricted Boltzmann Machine is one of sophisticated types of neural networks, which can process the probability distribution, and is applied to filtering image recognition and modelling. The learning procedure is based on the matrix description of RBM, where the learning samples are grouped into packages, and represented as matrices. Our research confirms a potential usefulness for video key frame detection. The proposed method provides better results for professional and high-resolution videos. The simulations we conducted proved the effectiveness of our approach. The algorithm requires only one input parameter.
    Źródło:
    Journal of Applied Mathematics and Computational Mechanics; 2015, 14, 3; 49-58
    2299-9965
    Pojawia się w:
    Journal of Applied Mathematics and Computational Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    System Concept of WIFI Based Passive Radar
    Autorzy:
    Rzewuski, S.
    Kulpa, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/227053.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    passive radar system
    WIFI signal decoding
    frame detection
    processing signal from wireless networks
    Opis:
    In this paper idea of passive radar system based on popular wireless networks commonly named WIFI is presented. In such an networks many transmitters operates in the same channel using multiple access. Wireless networks operating on frequencies 2.4GHz and 5GHz are very common today (IEEE 802.11 a/b/g/n). Classic passive radar determines bistatic distance and velocity by using cross-ambiguity function. To seek target position in XYZ space at least illumination of 3 different transmitters is required. In that paper it was assumed, that all transmitters operate on the same band frequency and the passive radar receiver has to couple each transmission burst with transmitter position by decoding the physical address of transmitter from captured data stream. Having most of the signal sources in our passive radar environment it is possible to detect and to localize objects of interest.
    Źródło:
    International Journal of Electronics and Telecommunications; 2011, 57, 4; 447-450
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Detection of Montage in Lossy Compressed Digital Audio Recordings
    Autorzy:
    Korycki, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/177075.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    tampering detection
    digital forgeries
    digital audio authenticity
    lossy compression
    frame offsets
    modified discrete cosine transform
    MDCT
    advanced audio coding
    AAC
    ogg vorbis
    Opis:
    This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. Presented approach is based on frame offset measurement in audio files compressed and decoded by using perceptual audio coding algorithms which employ modified discrete cosine transform. The minimum values of total number of active MDCT coefficients occur for frame shifts equal to multiplications of applied window length. Any modification of audio file, including cutting off or pasting a part of audio recording causes a disturbance within this regularity. In this study the algorithm based on checking frame offset previously described in the literature is expanded by using each of four types of analysis windows commonly applied in the majority of MDCT based encoders. To enhance the robustness of the method additional histogram analysis is performed by detecting the presence of small value spectral components. Moreover, computation of maximum values of nonzero spectral coefficients is employed, which creates a gating function for the results obtained based on previous algorithm. This solution radically minimizes a number of false detections of forgeries. The influence of compression algorithms’ parameters on detection of forgeries is presented by applying AAC and Ogg Vorbis encoders as examples. The effectiveness of tampering detection algorithms proposed in this paper is tested on a predefined music database and compared graphically using ROC-like curves.
    Źródło:
    Archives of Acoustics; 2014, 39, 1; 65-72
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Real-time Foreground Object Detection Combining the PBAS Background Modelling Algorithm and Feedback from Scene Analysis Module
    Autorzy:
    Kryjak, T.
    Komorkiewicz, M.
    Gorgon, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/225985.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    PBAS algorithm
    foreground segmentation
    foreground object detection
    background generation
    background subtraction
    background modelling
    image processing
    image analysis
    FPGA
    connected component analysis
    consecutive frame diffrencing
    Opis:
    The article presents a hardware implementation of the foreground object detection algorithm PBAS (Pixel-Based Adaptive Segmenter) with a scene analysis module. A mechanism for static object detection is proposed, which is based on consecutive frame differencing. The method allows to distinguish stopped foreground objects (e.g. a car at the intersection, abandoned luggage) from false detections (so-called ghosts) using edge similarity. The improved algorithm was compared with the original version on popular test sequences from the changedetection.net dataset. The obtained results indicate that the proposed approach allows to improve the performance of the method for sequences with the stopped objects. The algorithm has been implemented and successfully verified on a hardware platform with Virtex 7 FPGA device. The PBAS segmentation, consecutive frame differencing, Sobel edge detection and advanced one-pass connected component analysis modules were designed. The system is capable of processing 50 frames with a resolution of 720×576 pixels per second.
    Źródło:
    International Journal of Electronics and Telecommunications; 2014, 60, 1; 61-72
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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