• Title/Summary/Keyword: Multi-view descriptors

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Integrating Multi-view Stereoscopic Transmission System into MPEG-21 DIA (Digital Item Adaptation)

  • Lee, Seung-Won;Kim, Man-Bae;Byun, Hye-Ran;Park, Il-Kwon
    • Journal of Broadcast Engineering
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    • v.12 no.4
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    • pp.342-349
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    • 2007
  • In general multi-view system, all the view sequences acquired at the server are transmitted to the client. However, this kind of system requires high processing power of the server as well as the client, thus it is posing a difficulty in practical applications. To overcome this problem, a relatively simple method is to transmit only two view-sequences requested by the client in order to deliver a stereoscopic video. In this system, effective communication between the server and the client is one of important aspects. Therefore, we propose an efficient multi-view system that transmits two view-sequences according to user's request. The view selection process is integrated into MPEG-21 DIA (Digital Item Adaptation) so that our system is compatible to MPEG-21 multimedia framework. Furthermore, multi-view descriptors related to multi-view camera and systems are newly introduced. The syntax of the descriptions and their elements is represented in XML (extensible Markup Language) schema. Intermediate view reconstruction (IVR) is used to reduce such discomfort with excessive disparity. Furthermore, IVR is useful for smooth transition between two stereoscopic view sequences. Finally, through the implementation of testbed, we can show the valuables and possibilities of our system.

Lung Sound Classification Using Hjorth Descriptor Measurement on Wavelet Sub-bands

  • Rizal, Achmad;Hidayat, Risanuri;Nugroho, Hanung Adi
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1068-1081
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    • 2019
  • Signal complexity is one point of view to analyze the biological signal. It arises as a result of the physiological signal produced by biological systems. Signal complexity can be used as a method in extracting the feature for a biological signal to differentiate a pathological signal from a normal signal. In this research, Hjorth descriptors, one of the signal complexity measurement techniques, were measured on signal sub-band as the features for lung sounds classification. Lung sound signal was decomposed using two wavelet analyses: discrete wavelet transform (DWT) and wavelet packet decomposition (WPD). Meanwhile, multi-layer perceptron and N-fold cross-validation were used in the classification stage. Using DWT, the highest accuracy was obtained at 97.98%, while using WPD, the highest one was found at 98.99%. This result was found better than the multi-scale Hjorth descriptor as in previous studies.