Tag Archives: Computer Vision

Books

I am the co-author of two book chapters.

  • [PDF] [DOI] J. Benois-Pineau, A. Bugeau, S. Karaman, and R. Mégret, “Spatial and multi-resolution context in visual indexing,” in Visual Indexing and Retrieval, J. Benois-Pineau, F. Precioso, and M. Cord, Eds., Springer New York, 2012, pp. 41-63.
    [Bibtex]
    @incollection{BenoisSpatial2012,
    author = {Benois-Pineau, Jenny and Bugeau, Aurélie and Karaman, Svebor and Mégret, Rémi},
    title = {Spatial and multi-resolution context in visual indexing},
    booktitle = {Visual Indexing and Retrieval},
    editor = {Benois-Pineau, Jenny and Precioso, Frédéric and Cord, Matthieu},
    isbn = {978-1-4614-3587-7},
    series = {SpringerBriefs in Computer Science},
    doi = {10.1007/978-1-4614-3588-4_4},
    url = {http://dx.doi.org/10.1007/978-1-4614-3588-4_4},
    publisher = {Springer New York},
    pages = {41-63},
    language = {English},
    year = {2012}
    }
  • [PDF] [DOI] S. Karaman, G. Lisanti, A. D. Bagdanov, and A. Del Bimbo, “From Re-identification to Identity Inference: Labeling Consistency by Local Similarity Constraints,” in Person Re-Identification, S. Gong, M. Cristani, S. Yan, and C. C. Loy, Eds., Springer London, 2014, pp. 287-307.
    [Bibtex]
    @incollection{KaramanReID2014,
    author = {Karaman, Svebor and Lisanti, Giuseppe and Bagdanov, Andrew D. and Del Bimbo, Alberto},
    title = {From Re-identification to Identity Inference: Labeling Consistency by Local Similarity Constraints},
    booktitle = {Person Re-Identification},
    series = {Advances in Computer Vision and Pattern Recognition},
    editor = {Gong, Shaogang and Cristani, Marco and Yan, Shuicheng and Loy, Chen Change},
    isbn = {978-1-4471-6295-7},
    doi = {10.1007/978-1-4471-6296-4_14},
    url = {http://dx.doi.org/10.1007/978-1-4471-6296-4_14},
    publisher = {Springer London},
    keywords = {Re-identification; Identity inference; Conditional random fields; Video surveillance},
    pages = {287-307},
    language = {English},
    year = {2014}
    }
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About me

I am a French Computer Vision and Machine Learning researcher, currently a  Research Manager at Dataminr. Previously, I spent three years as a PostDoc at the MICC (Media Integration and Communication Center) of the University of Florence in Italy, and five years as an Associate Research Scientist in the DVMM Lab at Columbia University.

Research themes

My research themes are image and video analysis, computer vision, and machine learning. I am particularly interested in semantic concept recognition in images and videos.

I did my Ph.D. at the LaBRI – University of Bordeaux, under the supervision of Jenny Benois-Pineau and Rémi Mégret. During my Ph.D. thesis, I worked on human activity recognition by Hidden Markov Models (HMM) in videos recorded from a wearable device within the IMMED project. I have also developed an object recognition approach in the Bag-of-Visual-Words framework which integrates spatial information within semi-local features: the Graph-Words. I defended my Ph.D. entitled “Indexing of Activities in Wearable Videos: Application to Epidemiological Studies of Aged Dementia” in 2011.

While at the MICC, I have been highly involved in the MNEMOSYNE project. In this project, multiple aspects of computer vision such as person detection, person tracking, and re-identification are used to passively profile the interests of visitors in a museum to provide personalized multimedia content delivery. I was also working on more general image and video classification problems.

At the DVMM Lab, I have been working mostly on large-scale image indexing and retrieval problems but I also published works on other projects such as social media understanding, grounding, scene graph generation, visual parsing, and GAN detections…

At Dataminr, I’m working on computer vision and multimodal-related problems.

Keywords

Computer Vision, Machine Learning, Image Analysis, Video Analysis, Video Indexing, Object Recognition, Person Detection, Re-Identification, Passive Profiling, Behavior Analysis, Action Recognition…