Summary
In this chapter a knowledge-assisted, domain-specific video analysis framework is introduced and employed for content-adaptive video coding and transmission. Domain knowledge employed under the proposed framework considers both low-level features and spatial behavior of video content for the purpose of analysis, as well as domain-, application- and user-specific importance factors associated with each domain concept that guide content-adaptive coding and transmission. The analysis approach relies on a genetic algorithm for supporting efficient object localization and identification with the use of domain knowledge. The application of the genetic algorithm is preceded by the automatic generation of a set of atom-regions by means of segmentation and the subsequent extraction of the atom-region lowlevel descriptors. The output of the analysis process is used for the content-adaptive optimization of the coding and transmission of the video. Several methodologies for the coding and transmission of video over unreliable wireline and wireless channels are presented, utilizing advanced channel coding techniques for unequally protecting the objects of the video stream on the basis of the importance factors defined in the domain knowledge. Experimental results on a test set comprising Formula One and Tennis domain videos demonstrate the effectiveness of the proposed framework.
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U. Gargi, R. Kasturi, and S.H. Strayer, “Performance Characterization of Video-Shot-Change Detection Methods,” IEEE Transaction on Circuits and Systems for Video Technology, vol. 10, no. 1, pp. 1–13, Feb 2000.
V. Mezaris, I. Kompatsiaris, and M.G. Strintzis, “Still Image Segmentation Tools for Object-based Multimedia Applications,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 18, no. 4, pp. 701–725, June 2004.
V. Mezaris, I. Kompatsiaris, N.V. Boulgouris, and M.G. Strintzis, “Real-Time Compressed-Domain Spatiotemporal Segmentation and Ontologies for Video Indexing and Retrieval,” IEEE Transaction on Circuits and Systems for Video Technology, vol. 14, no. 5, pp. 606–621, May 2004.
S.-Y. Chien, Y.-W. Huang, B.-Y. Hsieh, S.-Y. Ma, and L.-G. Chen, “Fast Video Segmentation Algorithm with Shadow Cancellation, Global Motion Compensation, and Adaptive Threshold Techniques,” IEEE Transactions on Multimedia, vol. 6, no. 5, pp. 732–748, Oct 2004.
T. Gruber, “A Translation Approach to Portable Ontology Specifications,” Knowledge Acquisition, vol. 5, no. 2, pp. 199–220, 1993.
J. Assfalg, M. Berlini, A. Del Bimbo, W. Nunziat, and P. Pala, “Soccer Highlights Detection and Recognition using HMMs,” in IEEE International Conference on Multimedia and Expo (ICME), pp. 825–828, 2005.
L. Zhang, F.Z. Lin, and B. Zhang, “Support Vector Machine Learning for Image Retrieval,” in IEEE International Conference on Image Processing (ICIP), pp. 721–724, 2001.
J. Hunter, J. Drennan, and S. Little, “Realizing the Hydrogen Economy through Semantic Web Technologies,” IEEE Intelligent Systems Journal - Special Issue on eScience, vol. 19, pp. 40–47, 2004.
A. Yoshitaka, S. Kishida, M. Hirakawa, and T. Ichikawa, “Knowledge-Assisted Content-Based Retrieval for Multimedia Databases,” IEEE Multimedia, vol. 1, no. 4, pp. 12–21, Winter 1994.
G. Tsechpenakis, G. Akrivas, G. Andreou, G. Stamou, and S.D. Kollias, “Knowledge-Assisted Video Analysis and Object Detection,” in Proceedings of European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems (Eunite02), Algarve, Portugal, Sep. 2002.
M. Ramesh Naphade, I.V. Kozintsev, and T.S. Huang, “A Factor Graph Framework for Semantic Video Indexing,” IEEE Transaction on Circuits and Systems for Video Technology, vol. 12, no. 1, pp. 40–52, Jan. 2002.
S. Dasiopoulou, C. Doulaverakis, V. Mezaris, I. Kompatsiaris, and M. G. Strintzis, “An Ontology-Based Framework for Semantic Image Analysis and Retrieval,” Semantic-based Visual Information Retrieval, Y.-J. Zhang (Ed.), 2007.
D.A. Randell, Z. Cui, and A.G. Cohn, “A Spatial Logic Based on Regions and Connection.,” in KR, pp. 165–176, 1992.
M.J. Egenhofer and R.D. Franzosa, “Point Set Topological Relations.,” International Journal of Geographical Information Systems, vol. 5, pp. 161–174, 1991.
B.S. Manjunath, J.-R. Ohm, V.V. Vasudevan, and A. Yamada, “Color and Texture Descriptors,” IEEE Transaction on Circuits and Systems for Video Technology, special issue on MPEG-7, vol. 11, no. 6, pp. 703–715, June 2001.
M. Bober, “MPEG-7 visual shape descriptors,” IEEE Transaction on Circuits and Systems for Video Technology, special issue on MPEG-7, vol. 11, no. 6, pp. 716–719, June 2001.
J. McQueen, “Some Methods for Classification and Analyis of Multivariate Observations,” in 5th Berkely Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–296, 1967.
T. Yu and Y. Zhang, “Retrieval of Video Clips using Global Motion Information,” Electronics Letters, vol. 37, no. 14, pp. 893–895, July 2001.
F. Precioso, M. Barlaud, T. Blu, and M. Unser, “Smoothing B-Spline Active Contour for Fast and Robust Image and Video Segmentation.,” in ICIP (1), pp. 137–140, 2003.
MPEG-7 XM software, “http://www.lis.ei.tum.de/research/bv/topics/mmdb/ e_mpeg7.html,”.
M. Jacob, T. Blu, and M. Unser, “An Exact Method for Computing the Area Moments of Wavelet and Spline Curves.,” IEEE Transactions on Pattern Analalysis and Machine Intelligence, vol. 23, no. 6, pp. 633–642, 2001.
M. Mitchell, An introduction to Genetic Algorithms, MIT, 1996.
D. Goldberg and K. Deb, A comparative analysis of selection schemes used in genetic algorithms, pp. 69–93, G. Rawlins, 1991.
R. Gallager, “Low-Density Parity-Check Codes.,” IRE Transactions on Information Theory, pp. 21–28, Jan 1962.
C. Berrou and A. Glavieux, “Near Optimum Error Correcting Coding And Decoding: Turbo Codes,” IEEE Transaction on Communications, vol. 44, no. 10, pp. 1261–1271, Oct. 1996.
Y. Shoham and A. Gersho, “Efficient Bit Allocation for an Arbitrary Set of Quantizers,” IEEE Transaction on Acoustics, Speech, Signal Processing, vol. 36, pp. 1445–1453, Sep. 1988.
N.V. Boulgouris, N. Thomos, and M.G. Strintzis, “Transmission of Images Over Noisy Channels Using Error-Resilient Wavelet Coding and Forward Error Correction,” IEEE Transaction on Circuits and Systems for Video Technology, vol. 13, no. 12, pp. 1170–1181, Dec. 2003.
N. Thomos, N.V. Boulgouris, and M.G. Strintzis, “Wireless Image Transmission Using Turbo Codes and Optimal Unequal Error Protection,” IEEE Transaction on Image Processing, vol. 14, no. 11, pp. 1890–1901, Nov. 2005.
N. Thomos, N.V. Boulgouris, and M.G. Strintzis, “Product Code Optimization for Determinate State LDPC Decoding in Robust Image Transmission,” IEEE Transaction on Image Processing, vol. 15, no. 8, pp. 2113–2119, Aug. 2006.
G.D. Forney, “The Viterbi Algorithm,” Proceedings of IEEE, vol. 61, no. 3, pp. 268–278, Mar. 1973.
J.-C. Tuan, T.-S. Chang, and C.-W. Jen, “On the data reuse and memory bandwidth analysis for full-search block-matching VLSI architecture,” IEEE Transaction on Circuits and Systems for Video Technology, vol. 12, no. 1, pp. 61–72, Jan. 2002.
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Mezaris, V., Thomos, N., Boulgouris, N.V., Kompatsiaris, I. (2008). Knowledge-Assisted Analysis of Video for Content-Adaptive Coding and Transmission. In: Wallace, M., Angelides, M.C., Mylonas, P. (eds) Advances in Semantic Media Adaptation and Personalization. Studies in Computational Intelligence, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76361_11
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DOI: https://doi.org/10.1007/978-3-540-76361_11
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