Abstract
This paper describes an innovative compression method of panoramic images based on MPEG-7 descriptors. The proposed solution employs a detection of a series of individual video frame overlaps in order to produce concatenated panoramic images. The presented method is easy to implement even in simple devices such as low power consuming chipsets installed in remote cameras having limited power supplies. Under subjective tests it has been proved that the concatenation method allows for achieving lower transmission rates while sustaining picture quality.












Similar content being viewed by others
References
Glowacz A, Grega M, Leszczuk M, Romaniak P (2006) Detecting panoramic image overlaps with MPEG-7 descriptors. In: Proceedings of the international conference on signals and electronic systems (ICSES ’06). Łódź, Poland
Halonen T, Romero J, Melero J (2003) GSM, GPRS and EDGE performance—evolution towards 3G/UMTS. Wiley, New York
Holma H, Toskala A (2004) WCDMA for UMTS. Wiley, New York
Hsieh JW (2004) Fast stitching algorithm for moving object detection and mosaic construction. Image Vis Comput 22:291–306
Hsu CT, Tsan YC (2004) Mosaics of video sequences with moving objects. Signal Process Image Commun 19:81–98
Huang F (2000) Epipolar geometry in concentric panoramas, research report CTU-CMP-2000-07. University of Auckland, Auckland, New Zealand
ISO Standard IS 14444-1:2004 (2004) Information technology—JPEG 2000 image coding system: core coding system
ISO Standard IS 14496-10 (2004) Information technology—coding of audio-visual objects—part 10: advanced video coding
ISO Standard IS 14496-2 (2004) Information technology—coding of audio-visual objects—part 2: visual
ISO/IEC Standard TR 15938 (2005) Information technology—multimedia content description interface
ISO/IEC 15948 (2004). Information technology—computer graphics and image processing—portable network graphics (PNG): functional specification
ITU-R Recommendation BT.500-11 (2002) Methodology for the subjective assessment of the quality of television pictures. Geneva, Switzerland
ITU-R Recommendation H.264 (2005) Advanced video coding for generic audiovisual services
ITU-R Recommendation T.81 (1992) Information technology—digital compression and coding of continuous-tone still images—requirements and guidelines
ITU-T Recommendation P.800 (1996) Methods for subjective determination of transmission quality. Geneva, Switzerland
ITU-T Recommendation T.800 (2004) Information technology—JPEG 2000 image coding system: core coding system
Kaaranen H, Ahtiainen A, Laitinen L, Naghian S, Niemi V (2005) UMTS networks—architecture, mobility and services. Wiley, New York
Kamisetty C, Jawahar CV (2003) Multiview image compression using algebraic constraints. In: Proc. IEEE region 10 conference on convergent technologies (TENCON). Bangalore, India, pp 927–931
Kim DH, Yoon YI, Choi JS (2003) An efficient method to build panoramic image mosaics. Pattern Recogn Lett 24:2421–2429
Manjunath BS, Salembier P, Sikora T (2002) Introduction to MPEG-7 multimedia content description interface. Wiley, Chichester, England
McLauchlan PF, Jaenicke A (2003) Image mosaicing using sequential bundle adjustment. Image Vis Comput 20:751–759
Pardyka I (2006) Homography-based panoramic image sequence compression method. ICSES ’06. Lodz, Poland, pp 293–296
Pardyka I (2006) Panoramic image sequence compression method. Visualization, Imaging, and Image Processing (VIIP 2006). ACTA, Mallorca, Spain, pp 282–286
Shah M, Javed O, Shafique K (2007) Automated visual surveillance in realistic scenarios. IEEE Multimedia 14(1):30–39
Szeliski R (2006) Image alignment and stitching: a tutorial. Foundations Trends Comput Graphics Vis 2(1):1–104
Tian GY, Gledhill D, Taylor D (2003) Comprehensive interest points based imaging mosaic. Pattern Recogn Lett 24:1171–1179
Trakaa M, Tziritasa G (2003) Panoramic view construction. Signal Process Image Commun 18:465–481
Zhang C, Long Y, Kurdahi F (2005) Embedded computer systems: architectures, modeling, and simulation. In: Proceedings of the 5th international workshop SAMOS (SAMOS ’05) (Samos, Greece, July 18–20, 2005). Springer, Lecture Notes in Computer Science, vol. 3553. Berlin/Heidelberg, p 334
Zitova B, Flusser J (2003) Image registration methods: a survey. Image Vis Comput 21:977–1000
Acknowledgements
The work presented in this paper was supported in part by the Polish State Ministry of Science and Higher Education under the Grants No. NN517438833 and 4T11D00525, as well as by the European Commission under the grant no. FP6-0384239 (Network of Excellence CONTENT).
Author information
Authors and Affiliations
Corresponding author
Appendix 1 Description of overlap coordinates detection algorithm
Appendix 1 Description of overlap coordinates detection algorithm
A recursive algorithm is implemented [1]. It starts with a zero translation vector: (x 0, y 0) = (0, 0). In the first step the x 1 coordinate is searched. This coordinate pinpoints the best place of intersection of images in the horizontal axis (with no vertical offset). A D(x 1, y 0) distance value of the overlapping at (x 1, y 0) image parts is calculated for evaluation of progress of the algorithm. After calculating the horizontal offset, a vertical offset is searched. For a found x 1 coordinate the y 1 coordinate is searched. A D(x 1, y 1) distance value of the overlapping at (x 1, y 1) image parts is calculated. If the result is better than the previous one, i.e. D(x 1, y 1) < D(x 1, y 0), the above algorithm is repeated, aiming at finding (x 2, y 1) with D(x 2, y 1). Otherwise, it terminates. The comparison of descriptor values calculated in the previous steps allows assessing if the result is closer to the optimal one. If any progress is made (the latter distance value is smaller than the previous one), the algorithm is continued. Otherwise, the previous coordinates pinpoint the best location for intersection of images. The algorithm is depicted in Fig. 3 in Section 2.2. Horizontal and vertical coordinates are calculated in a similar way.
Rights and permissions
About this article
Cite this article
Glowacz, A., Grega, M., Romaniak, P. et al. Compression and distribution of panoramic videos utilising MPEG-7-based image registration. Multimed Tools Appl 40, 321–339 (2008). https://doi.org/10.1007/s11042-008-0209-0
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-008-0209-0