Fabien Diot

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Dynamic graph mining is the task of searching for subgraph patterns that capture the evolution of a dynamic graph. In this paper, we are interested in mining dynamic graphs in videos. A video can be regarded as a dynamic graph, whose evolution over time is represented by a series of plane graphs, one graph for each video frame. As such, subgraph patterns in(More)
This paper shows a concrete example of the use of graph mining for tracking objects in videos with moving cameras and without any contextual information on the objects to track. To make the mining algorithm efficient, we benefit from a video representation based on dynamic (evolving through time) planar graphs. We then define a number of constraints to(More)
This paper shows how data mining and in particular graph mining and clustering can help to tackle difficult tracking problems such as tracking possibly multiple objects in a video with a moving camera and without any contextual information on the objects to track. Starting from different segmentations of the video frames (dynamic and non dynamic ones), we(More)
Faults and malfunctioning of HVAC systems in building can lead to important waste of energy, decrease of user’s comfort and deterioration of building and its facilities. These faults are sometime difficult to detect with present tools and can remain in the building during long period of time. The aim of our survey is to develop automatic Faults Detection(More)
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