SPATIO-TEMPORAL SEGMENTATION AND REGIONS TRACKING OF HIGH DEFINITION VIDEO SEQUENCES USING A MARKOV RANDOM FIELD MODEL

In such a situation, a classical approach consists in us- ing a neural network or a supervised classification as- sociated to a set of learning data corresponding to al- ready

Based on the presented model, our goal is to automatically select the cameras (fixed and mobile) that could contain relevant video content with regards to the

From top to bottom: (1) Input se- quence (with groundtruth overlaid); (2) Segmentation results from regular 3D MRFs with appearance-based observation model (544 pixels

The main forms of mobilities involved are the circulation of people, practices and ideas, the circula- tion of building types, the circulation of different kinds of media, such

The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of

One may wonder if the notion of state can be extended to handle such examples. For instance, in the FRAN frame- work [14] it is possible to express arbitrary equations on the date of

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Diana Nurbakova, Sylvie Calabretto, Léa Laporte, Jérôme Gensel?. To cite