VideoQ - A fully Automated Object-Oriented Content-based Video Search Engine

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VideoQ expands the traditional search methods (e.g., keywords and subject navigation) with a novel search technique that allows users to search video objects based on a rich set of visual features and spatio-temporal relationships. Our objective is to investigate the full potential of visual cues in object-oriented content-based video search. Some of the unique features of VideoQ include:

  • Automatic arbitray-shape video object segmentation and tracking.
  • A rich visual feature library including color, texture, shape, and motion.
  • Multi-object spatio-temporal video query (absolute and relative locations).

VideoQ currently supports a large database of digital videos. Individual videos are automatically segmented into separate shots. Currently, over 2000 shots are stored. Each shot is compressed and stored in three layers to meet different bandwidth requirements.

In addition to query by sketch, the user can browse the video shots or search video by text. The video shots are cataloged into a subject taxonomy, which the user can easily navigate. Each video shot has also been manually annotated so the user can perform simple text search of keywords.


Prof. Shih-Fu Chang, Di Zhong, William Chen, Hari Sundaram, Horace Meng




S.-F. Chang, W. Chen, H. J. Meng, H. Sundaram, and D. Zhong, VideoQ: An Automatic Content-Based Video Search System Using Visual Cues, Proceedings, ACM Multimedia '97 Conference, Seattle, WA, November 1997.

S.-F. Chang, W. Chen, H. J. Meng, H. Sundaram, and D. Zhong, A Fully Automated Content-Based Video Search Engine Supporting Spatio-Temporal Queries , IEEE Transactions on Circuits and Systems for Video Technology (CSVT), Vol. 8, No. 5, September 1998.

D. Zhong and S.-F. Chang, Video Object Model and Segmentation for Content-Based Video Indexing, IEEE International Symposium on Circuits and Systems (ISCAS'97), Hong Kong, June 1997, Special Session on Networked Multimedia Technology and Application.




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