Classifying Natural Objects on Outdoor Scenes

We propose an hybrid and probabilistic classification of image regions belonging to scenes primarily containing natural objects, e.g. sky, trees, etc. as a first step in solving the problem of scene context generation. Therefore, we will focus our work in the problem of image regions labeling to classify every pixel of a given image into one of several predefined classes. Our proposal begins with a top-down control to find the core of objects, which allow us to update the learned models. Moreover, they become the starting seeds for the growing of a set of concurrent active regions which, considering the own region model as well as region and boundary information, obtain an accurate recognition of known regions. Next, a general segmentation extracts the unknown regions by a bottom-up strategy. Finally, a last stage exploits the contextual information to classify initially unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a...

• Type: Conference
• Year: 2005
• Where: CCIA
• Authors: Anna Bosch, Xavier Muñoz, Joan Martí, Arnau Oliver
• Keywords: CCIA 2005, Concurrent Active Regions, Image Regions, Unknown Segmented Object