410 research outputs found

    Statistical feature extraction from compressed video sequences

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    Shot boundary detection in MPEG videos using local and global indicators

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    Shot boundary detection (SBD) plays important roles in many video applications. In this letter, we describe a novel method on SBD operating directly in the compressed domain. First, several local indicators are extracted from MPEG macroblocks, and AdaBoost is employed for feature selection and fusion. The selected features are then used in classifying candidate cuts into five sub-spaces via pre-filtering and rule-based decision making. Following that, global indicators of frame similarity between boundary frames of cut candidates are examined using phase correlation of dc images. Gradual transitions like fade, dissolve, and combined shot cuts are also identified. Experimental results on the test data from TRECVID'07 have demonstrated the effectiveness and robustness of our proposed methodology. * INSPEC o Controlled Indexing decision making , image segmentation , knowledge based systems , video coding o Non Controlled Indexing AdaBoost , MPEG videos , feature selection , global indicator , local indicator , rule-based decision making , shot boundary detection , video segmentation * Author Keywords Decision making , TRECVID , shot boundary detection (SBD) , video segmentation , video signal processing References 1. J. Yuan , H. Wang , L. Xiao , W. Zheng , J. L. F. Lin and B. Zhang "A formal study of shot boundary detection", IEEE Trans. Circuits Syst. Video Technol., vol. 17, pp. 168 2007. Abstract |Full Text: PDF (2789KB) 2. C. Grana and R. Cucchiara "Linear transition detection as a unified shot detection approach", IEEE Trans. Circuits Syst. Video Technol., vol. 17, pp. 483 2007. Abstract |Full Text: PDF (505KB) 3. Q. Urhan , M. K. Gullu and S. Erturk "Modified phase-correlation based robust hard-cut detection with application to archive film", IEEE Trans. Circuits Syst. Video Technol., vol. 16, pp. 753 2006. Abstract |Full Text: PDF (3808KB) 4. C. Cotsaces , N. Nikolaidis and I. Pitas "Video shot detection and condensed representation: A review", Proc. IEEE Signal Mag., vol. 23, pp. 28 2006. 5. National Institute of Standards and Technology (NIST), pp. [online] Available: http://www-nlpir.nist.gov/projects/trecvid/ 6. J. Bescos "Real-time shot change detection over online MPEG-2 video", IEEE Trans. Circuits Syst. Video Technol., vol. 14, pp. 475 2004. Abstract |Full Text: PDF (1056KB) 7. H. Lu and Y. P. Tan "An effective post-refinement method for shot boundary detection", IEEE Trans. Circuits Syst. Video Technol., vol. 15, pp. 1407 2005. Abstract |Full Text: PDF (3128KB) 8. G. Boccignone , A. Chianese , V. Moscato and A. Picariello "Foveated shot detection for video segmentation", IEEE Trans. Circuits Syst. Video Technol., vol. 15, pp. 365 2005. Abstract |Full Text: PDF (2152KB) 9. Z. Cernekova , I. Pitas and C. Nikou "Information theory-based shot cut/fade detection and video summarization", IEEE Trans. Circuits Syst. Video Technol., vol. 16, pp. 82 2006. Abstract |Full Text: PDF (1184KB) 10. L.-Y. Duan , M. Xu , Q. Tian , C.-S. Xu and J. S. Jin "A unified framework for semantic shot classification in sports video", IEEE Trans. Multimedia, vol. 7, pp. 1066 2005. Abstract |Full Text: PDF (2872KB) 11. H. Fang , J. M. Jiang and Y. Feng "A fuzzy logic approach for detection of video shot boundaries", Pattern Recogn., vol. 39, pp. 2092 2006. [CrossRef] 12. R. A. Joyce and B. Liu "Temporal segmentation of video using frame and histogram space", IEEE Trans. Multimedia, vol. 8, pp. 130 2006. Abstract |Full Text: PDF (864KB) 13. A. Hanjalic "Shot boundary detection: Unraveled and resolved", IEEE Trans. Circuits Syst. Video Technol., vol. 12, pp. 90 2002. Abstract |Full Text: PDF (289KB) 14. S.-C. Pei and Y.-Z. Chou "Efficient MPEG compressed video analysis using macroblock type information", IEEE Trans. Multimedia, vol. 1, pp. 321 1999. Abstract |Full Text: PDF (612KB) 15. C.-L. Huang and B.-Y. Liao "A robust scene-change detection method for video segmentation", IEEE Trans. Circuits Syst. Video Technol., vol. 11, pp. 1281 2001. Abstract |Full Text: PDF (241KB) 16. Y. Freund and R. E. Schapire "A decision-theoretic generalization of online learning and an application to boosting", J. Comput. Syst. Sci., vol. 55, pp. 119 1997. [CrossRef] On this page * Abstract * Index Terms * References Brought to you by STRATHCLYDE UNIVERSITY LIBRARY * Your institute subscribes to: * IEEE-Wiley eBooks Library , IEEE/IET Electronic Library (IEL) * What can I access? Terms of Us

    Dynamic adaptation of streamed real-time E-learning videos over the internet

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    Even though the e-learning is becoming increasingly popular in the academic environment, the quality of synchronous e-learning video is still substandard and significant work needs to be done to improve it. The improvements have to be brought about taking into considerations both: the network requirements and the psycho- physical aspects of the human visual system. One of the problems of the synchronous e-learning video is that the head-and-shoulder video of the instructor is mostly transmitted. This video presentation can be made more interesting by transmitting shots from different angles and zooms. Unfortunately, the transmission of such multi-shot videos will increase packet delay, jitter and other artifacts caused by frequent changes of the scenes. To some extent these problems may be reduced by controlled reduction of the quality of video so as to minimise uncontrolled corruption of the stream. Hence, there is a need for controlled streaming of a multi-shot e-learning video in response to the changing availability of the bandwidth, while utilising the available bandwidth to the maximum. The quality of transmitted video can be improved by removing the redundant background data and utilising the available bandwidth for sending high-resolution foreground information. While a number of schemes exist to identify and remove the background from the foreground, very few studies exist on the identification and separation of the two based on the understanding of the human visual system. Research has been carried out to define foreground and background in the context of e-learning video on the basis of human psychology. The results have been utilised to propose methods for improving the transmission of e-learning videos. In order to transmit the video sequence efficiently this research proposes the use of Feed- Forward Controllers that dynamically characterise the ongoing scene and adjust the streaming of video based on the availability of the bandwidth. In order to satisfy a number of receivers connected by varied bandwidth links in a heterogeneous environment, the use of Multi-Layer Feed-Forward Controller has been researched. This controller dynamically characterises the complexity (number of Macroblocks per frame) of the ongoing video sequence and combines it with the knowledge of availability of the bandwidth to various receivers to divide the video sequence into layers in an optimal way before transmitting it into network. The Single-layer Feed-Forward Controller inputs the complexity (Spatial Information and Temporal Information) of the on-going video sequence along with the availability of bandwidth to a receiver and adjusts the resolution and frame rate of individual scenes to transmit the sequence optimised to give the most acceptable perceptual quality within the bandwidth constraints. The performance of the Feed-Forward Controllers have been evaluated under simulated conditions and have been found to effectively regulate the streaming of real-time e-learning videos in order to provide perceptually improved video quality within the constraints of the available bandwidth
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