An Algorithmic Approach for General Video Summarization

In the current world, multimedia has a significant role in communicating information. Videos can convey more information. Two drawbacks of the video make it inconvenient in some circumstances. First, it requires more storage. Second, we require watching a video completely to identify the content, which takes too much time. Our proposed work makes the video easy to use by solving these issues. We are trying to reduce the volume of a video by creating its summary. Summarization may either produce a image/video as output. We generate a summary video. Duplicate frame removal and stroboscopic imaging are the main techniques used in the work. For better results, the shots identified at the initial step are further processed to create their own summary clips. Summary clips are clustered together to form the final summary. The result of the proposed work is a summary video with very limited number of frames. Our proposed work can generate summary for any type of videos such as entertainment, game, surveillance and home videos. The summary video keeps the continuity of the video and conveys the meaning too.

[1]  Uday B. Desai,et al.  Shot boundary detection in the presence of illumination and motion , 2013, Signal Image Video Process..

[2]  V. S. Subrahmanian,et al.  The priority curve algorithm for video summarization , 2004, MMDB '04.

[3]  Kristen Grauman,et al.  Story-Driven Summarization for Egocentric Video , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Michael R. Lyu,et al.  Semantic Video Summarization Using Mutual Reinforcement Principle and Shot Arrangement Patterns , 2005, 11th International Multimedia Modelling Conference.

[5]  David Salesin,et al.  Schematic storyboarding for video visualization and editing , 2006, SIGGRAPH 2006.

[6]  Georgios Tziritas,et al.  Equivalent Key Frames Selection Based on Iso-Content Principles , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Atsuo Yoshitaka,et al.  Video Summarization based on Film Grammar , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[8]  Chong-Wah Ngo,et al.  Video Summarization , 2009, Encyclopedia of Database Systems.

[9]  Yunhong Wang,et al.  Visual Saliency Based Aerial Video Summarization by Online Scene Classification , 2011, 2011 Sixth International Conference on Image and Graphics.

[10]  Chia-Hung Yeh,et al.  Techniques for movie content analysis and skimming: tutorial and overview on video abstraction techniques , 2006, IEEE Signal Processing Magazine.

[11]  Yael Pritch,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2008 1 Non-Chronological Video , 2022 .

[12]  P. R. Deshmukh,et al.  Keyframe Based Video Summarization Using Automatic Threshold & Edge Matching Rate , 2012 .

[13]  Yael Pritch,et al.  Making a Long Video Short: Dynamic Video Synopsis , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[14]  Jing Chen,et al.  User-Specific Video Summarization , 2011, 2011 International Conference on Multimedia and Signal Processing.

[15]  George Economou,et al.  Key frame extraction in video sequences: a vantage points approach , 2007, 2007 IEEE 9th Workshop on Multimedia Signal Processing.

[16]  David Salesin,et al.  Schematic storyboarding for video visualization and editing , 2006, SIGGRAPH '06.