International Conference on Multimedia Modeling

MultiMedia Modeling pp 377-382 | Cite as

IMOTION – Searching for Video Sequences Using Multi-Shot Sketch Queries

  • Luca Rossetto
  • Ivan Giangreco
  • Silvan Heller
  • Claudiu Tănase
  • Heiko Schuldt
  • Stéphane Dupont
  • Omar Seddati
  • Metin Sezgin
  • Ozan Can Altıok
  • Yusuf Sahillioğlu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9517)

Abstract

This paper presents the second version of the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. Ever since, IMOTION has supported the search for video sequences on the basis of still images, user-provided sketches, or the specification of motion via flow fields. For the second version, the functionality and the usability of the system have been improved. It now supports multiple input images (such as sketches or still frames) per query, as well as the specification of objects to be present within the target sequence. The results are either grouped by video or by sequence and the support for selective and collaborative retrieval has been improved. Special features have been added to encapsulate semantic similarity.

References

  1. 1.
    Collobert, R., Kavukcuoglu, K., Farabet, C.: Torch7: a matlab-like environment for machine learning. In: BigLearn, NIPS Workshop (2011)Google Scholar
  2. 2.
    Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.: HMDB: a large video database for human motion recognition. In: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2556–2563 (2011)Google Scholar
  3. 3.
    Rossetto, L., Giangreco, I., Schuldt, H.: Cineast: a multi-feature sketch-based video retrieval engine. In: Proceedings of the IEEE International Symposium on Multimedia (ISM 2014), pp. 18–23. IEEE (2014)Google Scholar
  4. 4.
    Rossetto, L., Giangreco, I., Schuldt, H., Dupont, S., Seddati, O., Sezgin, M., Sahillioğlu, Y.: IMOTION - a content-based video retrieval engine. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Abul Hasan, M. (eds.) MultiMedia Modeling. LNCS, vol. 8936, pp. 255–260. Springer, Heidelberg (2015)Google Scholar
  5. 5.
    Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. (IJCV), 1–42 (2015)Google Scholar
  6. 6.
    Schoeffmann, K., Ahlström, D., Bailer, W., Cobârzan, C., Hopfgartner, F., McGuinness, K., Gurrin, C., Frisson, C., Le, D.-D., Del Fabro, M., et al.: The video browser showdown: a live evaluation of interactive video search tools. Int. J. Multimed. Inf. Retr. 3(2), 113–127 (2014)Google Scholar
  7. 7.
    Seddati, O., Dupont, S., Mahmoudi, S.: Deepsketch: deep convolutional neural networks for sketch recognition and similarity search. In: Proceedings of the 13th International Workshop on Content-Based Multimedia Indexing (CBMI 2015), pp. 1–6. IEEE (2015)Google Scholar
  8. 8.
    Soomro, K., Zamir, A.R., Shah, M.: UCF101: a dataset of 101 human actions classes from videos in the wild. CoRR, abs/1212.0402 (2012)Google Scholar
  9. 9.
    Zhou, B., Lapedriza, A., Xiao, J., Torralba, A., Oliva, A.: Learning deep features for scene recognition using places database. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 27, pp. 487–495. Curran Associates Inc. (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Luca Rossetto
    • 1
  • Ivan Giangreco
    • 1
  • Silvan Heller
    • 1
  • Claudiu Tănase
    • 1
  • Heiko Schuldt
    • 1
  • Stéphane Dupont
    • 2
  • Omar Seddati
    • 2
  • Metin Sezgin
    • 3
  • Ozan Can Altıok
    • 3
  • Yusuf Sahillioğlu
    • 3
  1. 1.Databases and Information Systems Research Group, Department of Mathematics and Computer ScienceUniversity of BaselBaselSwitzerland
  2. 2.Research Center in Information TechnologiesUniversité de MonsMonsBelgium
  3. 3.Intelligent User Interfaces LabKoç UniversityIstanbulTurkey

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