Abstract
This paper presents an interactive tool for searching a known item in a video or a video archive. To rapidly select the relevant segment, we use query patterns formulated by users for filtering. The patterns can be formulated by drawing color sketches or selecting predefined concepts. Especially, our tool support users to define patterns for sequences of consecutive segments, for instance, sequences of occurrences of concepts. Such patterns are called sequential patterns, which are more powerful to describe users’ search intention. Besides that, the user interface is organized following a coarse-to-fine manner, so that users can quickly scan the set of candidate segments. By using color-based and concept-based filters, our tool can deal with both visual and descriptive known item search.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Le, D.-D., Lam, V., Ngo, T.D., Tran, V.Q., Nguyen, V.H., Duong, D.A., Satoh, S.: NII-UIT-VBS: A Video Browsing Tool for Known Item Search. In: Li, S., El Saddik, A., Wang, M., Mei, T., Sebe, N., Yan, S., Hong, R., Gurrin, C. (eds.) MMM 2013, Part II. LNCS, vol. 7733, pp. 547–549. Springer, Heidelberg (2013)
Scott, D., et al.: DCU at MMM 2013 Video Browser Showdown. In: Li, S., El Saddik, A., Wang, M., Mei, T., Sebe, N., Yan, S., Hong, R., Gurrin, C. (eds.) MMM 2013, Part II. LNCS, vol. 7733, pp. 541–543. Springer, Heidelberg (2013)
Bai, H., Wang, L., Dong, Y., Tao, K.: Interactive Video Retrieval Using Combination of Semantic Index and Instance Search. In: Li, S., El Saddik, A., Wang, M., Mei, T., Sebe, N., Yan, S., Hong, R., Gurrin, C. (eds.) MMM 2013, Part II. LNCS, vol. 7733, pp. 554–556. Springer, Heidelberg (2013)
Viola, P., Jones, M.: Robust Real-time Face Detection. International Journal of Computer Vision (IJCV), 137–154 (2004)
Felzenszwalb, P., Girshick, R., McAllester, D., Ramanan, D.: Object Detection with Discriminatively Trained Part Based Models. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 1627–1645 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Ngo, T.D. et al. (2014). NII-UIT: A Tool for Known Item Search by Sequential Pattern Filtering. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8326. Springer, Cham. https://doi.org/10.1007/978-3-319-04117-9_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-04117-9_50
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04116-2
Online ISBN: 978-3-319-04117-9
eBook Packages: Computer ScienceComputer Science (R0)