Low Level Analysis of Video Using Spatiotemporal Pixel Blocks

  • Umut Naci
  • Alan Hanjalic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4105)


Low-level video analysis is an important step for further semantic interpretation of the video. This provides information about the camera work, video editing process, shape, texture, color and topology of the objects and the scenes captured by the camera. Here we introduce a framework capable of extracting the information about the shot boundaries and the camera and object motion, based on the analysis of spatiotemporal pixel blocks in a series of video frames. Extracting the motion information and detecting shot boundaries using the same underlying principle is the main contribution of this paper. Besides, this original principle is likely to improve robustness of the abovementioned low-level video analysis as it avoids typical problems of standard frame-based approaches and the camera motion information provides critical help to improve the shot boundary detection performance. The system is evaluated using TRECVID data [1] with promising results.


Motion Vector Shot Boundary Serve Time Interval Shot Transition Motion Estimation Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Umut Naci
    • 1
  • Alan Hanjalic
    • 1
  1. 1.Department of Mediamatics , ICT GroupDelft University of Technology, Faculty of EEMCSDelftThe Netherlands

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