Indexing images or videos from their content

In light of the explosion of images and videos that are produced, archived and exchanged on the Internet and in private networks, the manual annotation of their content has become an impossible task. To overcome this hurdle, we contribute to developing technologies that allow for indexing and searching images and videos according to the visual elements they contain. For example, the underlying faces, textual content and places can be recognized by our software. Coherent storage and retrieval of information is achieved through the use of standard, yet evolved metadata formats such as MPEG-7 and RDF.

Related technologies: Test bed for the audio-visual MPEG-7 indexing of documentary films, test bed for indexing and searching filming locations, manual annotation software for generating the visual objects ground-truth in videos, same location image matching engine.

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Recent news

  • CRIM Blog - Deep learning applied to graphs
    16/10/2018

    An article by Jade Guisiano, data science intern at CRIM.

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Upcoming event

  • ICTAC 2018
    19 October 2018 0:00
    Stellenbosch, Afrique du Sud
    CRIM will present a paper at the 15th International Colloquium on the Theoretical Aspects of Computing to take place 16-19 October 2018 in Stellenbosch, South Africa.
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Recent Publications

  • Towards Automatic Feature Extraction for Activity Recognition from Wearable Sensors: A Deep Learning Approach

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  • État des lieux des technologies web

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