VideoGraph: a new tool for video mining and classification

ABSTRACT

This paper introduces Videograph, a new tool for video mining and visu alizing the structure of the plot of a video sequence. The main idea is to &lquo;stitch&rquo; together similar scenes which are apart in time. We give a fast algorithm to do stitching and we show case studies, where our approach (a) gives good features for classification (91\% accuracy), and (b) results in Videographs which reveal the logical structure of the plot of the video clips.

REFERENCES

• 1: Christos Faloutsos , King-Ip Lin, FastMap: a fast algorithm for indexing, data-mining and visualization of traditional and multimedia datasets, Proceedings of the 1995 ACM SIGMOD international conference on Management of data, p.163-174, May 22-25, 1995, San Jose, California, United States
• 2: Vikrant Kobla , David Doermann , Christos Faloutsos, VideoTrails: representing and visualizing structure in video sequences, Proceedings of the fifth ACM international conference on Multimedia, p.335-346, November 09-13, 1997, Seattle, Washington, United States [doi>10.1145/266180.266384]
• 3: R. Kohavi, D. Sommerfield, and J. Dougherty. Data mining using MLC++: A machine learning library in C++. Tools with Artificial Intelligence, http://www.sgi.com/Technology/mlc.
• 4: Howard D. Wactlar , Michael G. Christel , Yihong Gong , Alexander G. Hauptmann, Lessons Learned from Building a Terabyte Digital Video Library, Computer, v.32 n.2, p.66-73, February 1999 [doi>10.1109/2.745722]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL

Additional Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods

  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Classifier design and evaluation

General Terms:
Algorithms, Design, Documentation, Experimentation, Human Factors, Management, Performance, Theory