IMOTION -A Content-Based Video Retrieval Engine

详细信息    查看全文

• 作者：Luca Rossetto (20)
  Ivan Giangreco (20)
  Heiko Schuldt (20)
  Stéphane Dupont (21)
  Omar Seddati (21)
  Metin Sezgin (22)
  Yusuf Sahillio?lu (22)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：8936
• 期：1
• 页码：255-260
• 全文大小：315 KB
• 参考文献：1. Giangreco, I., Kabary, I.A., Schuldt, H.: ADAM -A Database and Information Retrieval System for Big Multimedia Collections. In: Proc. Int. Congr. on Big Data 2014 (BigData 2014), Anchorage, USA. IEEE (2014)
  2. IMOTION project, https://imotion-project.eu/
  3. Kasutani, E., Yamada, A.: The MPEG-7 Color Layout Descriptor: A Compact Image Feature Description for High-Speed Image/Video Segment Retrieval. In: Proc. Int. Conf. on Image Processing (ICIP 2001), Thessaloniki, Greece, pp. 674-77. IEEE (2001)
  4. Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet Classification with Deep Convolutional Neural Networks. In: Pereira, F., Burges, C.J.C., Bottou, L., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 25: Proc. Conf. on Neural Information Processing Systems (NIPS 2012), Lake Tahoe, USA, pp. 1097-105 (2012)
  5. Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.: HMDB: A Large Video Database for Human Motion Recognition. In: Proc. Int. Conf. on Computer Vision (ICCV 2011), Barcelona, Spain, pp. 2556-563. IEEE (2011)
  6. Park, D.K., Jeon, Y.S., Won, C.S.: Efficient Use of Local Edge Histogram Descriptor. In: Proc. Ws. on Multimedia, Los Angeles, USA, pp. 51-4. ACM (2000)
  7. Rossetto, L., Giangreco, I., Schuldt, H.: Cineast: A Multi-Feature Sketch-Based Video Retrieval Engine. In: Proc. Int. Symp. on Multimedia (ISM 2014), Taichung, Taiwan. IEEE (December 2014)
  8. Russakovsky, O., Deng, J., Su, H., et al.: ImageNet Large Scale Visual Recognition Challenge. CoRR, abs/1409.0575 (2014)
  9. Schüldt, C., Laptev, I., Caputo, B.: Recognizing Human Actions: A Local SVM Approach. In: Proc. Int. Conf. on Pattern Recognition (ICPR 2004), Cambridge, England, pp. 32-6. IEEE (2004)
  10. 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)
  
• 作者单位：Luca Rossetto (20)
  Ivan Giangreco (20)
  Heiko Schuldt (20)
  Stéphane Dupont (21)
  Omar Seddati (21)
  Metin Sezgin (22)
  Yusuf Sahillio?lu (22)
  
  20. Databases and Information Systems Research Group, Department of Mathematics and Computer Science, University of Basel, Switzerland
  21. Research Center in Information Technologies, Université de Mons, Belgium
  22. Intelligent User Interfaces Lab, Ko? University, Turkey
  
• ISSN：1611-3349

文摘

This paper introduces the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. For vector space retrieval, the IMOTION system exploits a large variety of low-level image and video features, as well as high-level spatial and temporal features that can all be jointly used in any combination. In addition, it supports dedicated motion features to allow for the specification of motion within a video sequence. For query specification, the IMOTION system supports query-by-sketch interactions (users provide sketches of video frames), motion queries (users specify motion across frames via partial flow fields), query-by-example (based on images) and any combination of these, and provides support for relevance feedback.