{"references": ["Nam Ling, \"Expectations and Challenges for Next Generation Video\nCompression\", 5th IEEE Conf. on Industrial Electronics and\nApplications, pp. 2339-2344, 2010.", "Wiegand, T., Sullivan, G. J., Bjontegard, G., et al., \"Overview of the\nH.264/AVC video coding standard\", IEEE Trans. on CSVT, vol. 13, no.\n7, pp. 560-576, 2003.", "Sullivan, G. and Wiegand, T., \"Video compression - from concepts to\nthe H.264/AVC standard\", Proc. of the IEEE, vol. 93, pp. 18-31, 2005.", "Jungwoo Lee et al., \"Rate-Distortion Optimized Frame Type Selection\nfor MPEG Encoding\", IEEE Transactions on Circuits and Systems for\nVideo Technology, vol. 7, no. 3, 1997.", "Jiro Katto, \"Mathematical analysis of MPEG compression capability and\nits application to rate control\", Int. Conf. of Image Processing-95, vol.\n11, pp. 555-558, 1995.", "Sowmyayani, S, Arockia Jansi Rani, P., \"Adaptive GOP structure to\nH.264/AVC based on Scene change\", ICTACT journal on image and\nvideo processing: special issue on video processing for multimedia\nsystems, vol. 5, no. 1, pp. 868-872, 2014.", "Shilpa Metkar, Sanjay Talbar, \"Motion Estimation Techniques for\nDigital Video Coding\" Springer Briefs in Applied Sciences and\nTechnology, Computational Intelligence, 2013", "Lin, Y. C. Tai, S. C., \"Fast full-search block-matching algorithm for\nmotion-compensated video compression\", IEEE Trans. Communication,\nvol. 45, no. 5, pp. 527\u2013531, 1997.", "Jong-Nam Kim and Tae-Sun Choi, \"A Fast Three Step Search\nAlgorithm with Minimum Checking Points\", Proc. of IEEE conf. on\nConsumer Electronics, vol. 2, no. 4, pp.132-133, 1998.\n[10] Li, R., Zeng, B., Liou, M. L., \"A new three step search algorithm for\nblock motion estimation\", IEEE Trans. Circuits Syst. Video Technol.,\nvol.4, no.4, pp. 438\u2013442, 1994.\n[11] Jianhua Lu, Ming L. Liou, \"A Simple and Efficient Search Algorithm\nfor Block-Matching Motion Estimation\", IEEE Trans. Circuits And\nSystems For Video Technology, vol. 7, no. 2, pp. 429-433, 1997.\n[12] Po, L.M., Ma, W.C., \"A novel four-step search algorithm for fast block\nmotion estimation\", IEEE Trans. Circuits Syst. Video Technol., vol. 6,\nno. 3, pp. 313\u2013317, 1996.\n[13] Ghanbari, M., \"The Cross-Search Algorithm for Motion Estimation\",\nIEEE Trans. on Communications, vol. 38, no. 1, pp. 950-953, 1990.\n[14] Zhu, S., Ma, K. K., \"A new diamond search algorithm for fast block\nmatching motion estimation\", IEEE Transactions on Image Processing,\nvol. 9, pp. 287\u2013290, 2000.\n[15] Zhu, C., Lin, X., Chau, L. P., \"Hexagon-based search pattern for fast\nblock motion estimation\", IEEE Trans. Circuits Syst. Video Technol.,\nvol. 12, no. 5, pp. 349\u2013355, 2002.\n[16] Faizul Haldi Jamil, Ali Chekima, Rosalyn R, et al., \"BMA Performance\nof video coding for motion estimation\", IEEE Trans. Int. Conf. on\nintelligent system modelling and simulation, 2012.\n[17] Cheung, C. H., Po, L. M., \"A novel cross-diamond search algorithm for\nfast block motion estimation\", IEEE Trans. on Circuits and Systems for\nVideo Technology, vol. 12, pp. 1168\u20131177, 2002.\n[18] Kamel Belloulata, Shiping Zhu, Zaikuo Wang, \"A Fast Fractal Video\nCoding Algorithm Using Cross-Hexagon Search for Block Motion\nEstimation\", Int. Scholarly Research Network.\n[19] Bei-li Zou, Cao Shi, Can-Hui Xu, et al., \"Enhanced Hexagonal-Based\nSearch Using Direction-Oriented Inner Search tor Motion Estimation\",\nIEEE Trans. on circuits and systems for video technology, vol. 20, no. 1,\n2010.\n[20] Cheung, C. H., Po, L. M., \"Novel cross-diamond-hexagonal search\nalgorithms for fast block motion estimation\", IEEE Trans. Multimedia,\nvol. 5, no. 1, pp. 16\u201322, 2005.\n[21] Chau, L. P., Zhu, C., \"A fast octagon \u2013based search algorithm for\nmotion estimation\", J. Signal Process, pp. 671\u2013675, 2003.\n[22] Chunjiang Duanmu, Yu Zhang, \"A New Fast Block Motion Algorithm\nBased on Octagon and Triangle Search Patterns for H.264/AVC\", Int.\nJournal of Digital Content Technology and its Applications, vol. 6,\nno.10, 2012.\n[23] Sangeeta Mishra, S., Chittaranjan Pradhan, Alka Singh, \"Comparative\nStudy of Motion Estimation Techniques in Video\", Int. Journal of\nComputer Science and Information Technologies, vol. 5, no. 3, pp.\n2982-2989, 2014.\n[24] Sowmyayani, S., Arockia Jansi Rani, P., \"Block based Motion\nEstimation using Octagon and Square Pattern\", Int. Journal of Signal\nProcessing, Image Processing and Pattern Recognition, vol. 7, no. 4, pp.\n317-324, 2014.\n[25] Lenka Krulikovsk\u00b4a and Jaroslav Polec, \"GOP Structure Adaptable to\nthe Location of Shotcuts\", Int. Journal of Electronics and\nTelecommunications, vol. 58, no. 2, pp. 129-134, 2012.\n[26] Joint Video Team (JVT) of ISO/IEC MPEG & ITU-T VCEG (ISO/IEC\nJTC1/SC29/WG11 and ITU-T SG16 Q.6) \"H.264/14496-10 AVC\nReference Software Manual (revised for JM 19.0)\", June 2015.\n[27] Lenka Krulikovska, Jaroslav Polec, and Michal Martinovic, \"Adaptive\nGroup of Pictures Structure Based On the Positions of Video Cuts\"\nWorld Academy of Science, Engineering and Technology International\nJournal of Computer, Information Science and Engineering, vol. 7, no.\n7, 2013.\n[28] Zatt, B., Porto, M., Scharcanski, J., et al., \"Gop structure adaptive to the\nvideo content for efficient H.264/AVC encoding\", Proc. of 2010 IEEE\n17th International Conference on Image Processing, pp.3053-3056,\n2010."]}

This paper integrates Octagon and Square Search pattern (OCTSS) motion estimation algorithm into H.264/AVC (Advanced Video Coding) video codec in Adaptive Group of Pictures (AGOP) mode. AGOP structure is computed based on scene change in the video sequence. Octagon and square search pattern block-based motion estimation method is implemented in inter-prediction process of H.264/AVC. Both these methods reduce bit rate and computational complexity while maintaining the quality of the video sequence respectively. Experiments are conducted for different types of video sequence. The results substantially proved that the bit rate, computation time and PSNR gain achieved by the proposed method is better than the existing H.264/AVC with fixed GOP and AGOP. With a marginal gain in quality of 0.28dB and average gain in bitrate of 132.87kbps, the proposed method reduces the average computation time by 27.31 minutes when compared to the existing state-of-art H.264/AVC video codec.