Research

Michael Mayer edited this page Dec 16, 2018 · 16 revisions

Links to related research projects and publications.

Slides

Personal Photo Selection

  • A. Ceroni, V. Solachidis, C. Niederée, O. Papadopoulou, N. Kanhabua, and V. Mezaris. To Keep or not to Keep: An Expectation-oriented Photo Selection Method for Personal Photo Collections. In Proceedings of the 5th ACM International Conference on Multimedia Retrieval, ICMR'15, 2015. [LINK]
  • A. Ceroni. (2018) Personal Photo Management and Preservation. In: Mezaris V., Niederée C., Logie R. (eds) Personal Multimedia Preservation - Remembering or Forgetting Images and Videos. Springer, Berlin, Heidelberg. [LINK]
  • Y. Wang, Z. Lin, X. Shen, R. Mech, G. Miller, and G. W. Cottrell. Event-specific image importance. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR'16, 2016. [LINK]
  • P. Sinha, S. Mehrotra, and R. Jain. Summarization of personal photologs using multidimensional content and context. In Proceedings of the 1st ACM International Conference on Multimedia Retrieval, ICMR'11, 2011. [LINK]
  • T. C. Walber, A. Scherp, and S. Staab. Smart photo selection: Interpret gaze as personal interest. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI'14, 2014. [LINK]
  • S. Tschiatschek, R. K. Iyer, H. Wei, and J. A. Bilmes. Learning mixtures of submodular functions for image collection summarization. In Proceedings of the 27th International Conference on Neural Information Processing Systems, NIPS '14, 2014. [LINK]
  • H. Yu, Z.H. Deng, Y. Yang, and T. Xiong. A joint optimization model for image summarization based on image content and tags. In Proceedings of the 28th AAAI Conference on Artificial Intelligence, AAAI '14, 2014. [LINK]
  • ForgetIT: Concise Preservation by combining Managed Forgetting and Contextualized Remembering

Event Recognition

  • K. Ahmad, N. Conci, G. Boato, and FGB De Natale. Event recognition in personal photo collections via multiple instance learning-based classification of multiple images. Journal of Electronic Imaging, 26(6), 2017. [LINK]
  • K. Ahmad, N. Conci, and FGB De Natale. A saliency-based approach to event recognition. Signal Processing: Image Communication, 60:42-51, 2018. [LINK]

Event-based Clustering

  • M. Zaharieva, M. Zeppelzauer, M. Del Fabro, and D. Schopfhauser. Social Event Mining in Large Photo Collections. In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, ICMR'15, 2015. [LINK]
  • C. Papagiannopoulou and V. Mezaris. Concept-based Image Clustering and Summarization of Event-related Image Collections. In Proceedings of the 1st ACM International Workshop on Human Centered Event Understanding from Multimedia (HuEvent '14), 2014. [LINK]
  • M. Cooper, J. Foote, A. Girgensohn, and L. Wilcox. Temporal event clustering for digital photo collections. ACM Trans. Multimedia Comput. Commun. Appl., 1(3):269-288, 2005. [LINK]

Near-duplicate Detection

  • J. Wang, Y. Song, T. Leung, C. Rosenberg, J. Philbin, B. Chen, and Y. Wu. Learning Fine-grained image similarity with deep ranking. In Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR '14, 2014. [LINK]
  • O. Chum, J. Philbin, and A. Zisserman. (2008). Near Duplicate Image Detection: min-Hash and tf-idf Weighting. In Proceedings of the British Machine Vision Conference 2008, BMVC'08. [LINK]
  • Y. Ke, R. Sukthankar, and L. Huston. An efficient parts-based near-duplicate and sub-image retrieval system. In Proceedings of the 12th annual ACM international conference on Multimedia, MM'04, 2004. [LINK]

Face Detection and Clustering

  • S. Yang, P. Luo, C. Loy, and X. Tang. From facial parts responses to face detection: A deep learning approach. In Proceedings of the IEEE International Conference on Computer Vision, ICCV'15, 2015. [LINK]
  • F. Schroff, D. Kalenichenko, and J. Philbin. Facenet: A unified embedding for face recognition and clustering. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR'15, 2015. [LINK]
  • C. Otto, D. Wang, and A. K. Jain. Clustering millions of faces by identity. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, 40(2), 2017. [LINK]

Image Quality and Aesthetics

  • S. Bosse, D. Maniry, K. Müller, T. Wiegand, and W. Samek. Deep neural networks for no-reference and full-reference image quality assessment. IEEE Transactions on Image Processing, 27(1), 206-219, 2018. [LINK]
  • L. Kang, P. Ye, Y. Li, and D. Doermann. Convolutional neural networks for no-reference image quality assessment. In Proceedings of the IEEE conference on computer vision and pattern recognition, CVPR'14, 2014. [LINK]
  • S. Dhar, V. Ordonez, and T. Berg. High level describable attributes for predicting aesthetics and interestingness. In Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR '11, pp. 1657-1664, 2011. [LINK]
  • E. Mavridaki and V. Mezaris. A comprehensive aesthetic quality assessment method for natural images using basic rules of photography. In Proceedings of the 2015 IEEE International Conference on Image Processing, ICIP '15, pp. 887-891, 2015. [LINK]
  • C. Yeh, Y. Ho, B. Barsky, and M. Ouhyoung. Personalized photograph ranking and selection system. In Proceedings of the 18th ACM International Conference on Multimedia, MM '10, pp. 211-220, 2010. [LINK]

Affective Image Classification

  • J. Machajdik, and A. Hanbury. Affective image classification using features inspired by psychology and art theory. In Proceedings of the 18th ACM international conference on Multimedia, MM'10, pp. 83-92, 2010. [LINK]
  • D. Borth, T. Chen, R. Ji, and S. Chang. Sentibank: large-scale ontology and classifiers for detecting sentiment and emotions in visual content. In Proceedings of the 21st ACM international conference on Multimedia, MM'13, pp. 459-460, 2013. [LINK]
  • S. Zhao, H. Yao, Y. Gao, R. Ji, and G. Ding. Continuous probability distribution prediction of image emotions via multitask shared sparse regression. IEEE Transactions on Multimedia, 19(3), pp. 632-645, 2017. [LINK]
  • Q. You, J. Luo, H. Jin, and J. Yang. Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and The Benchmark. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, AAAI'16, pp. 308-314, 2016. [LINK]

See also Ideas, Inbox, Related, Love, Concerns and Privacy.

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