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Bosch Rué, Anna
Muñoz Pujol, Xavier Martà BonmatÃ, Joan |
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We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal | |
http://hdl.handle.net/2072/58988 | |
eng | |
IEEE | |
Tots els drets reservats | |
Discriminació visual
Imatges -- Processament Imatges -- Segmentació Reconeixement òptic de formes Visió per ordinador Computer vision Image processing Imaging segmentation Optical pattern recognition Visual discrimination |
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Using appearance and context for outdoor scene object classification | |
info:eu-repo/semantics/article | |
Recercat |