In this paper we present a general framework for object detection
and segmentation. Using a bottom-up unsupervised merging algorithm,
a region-based hierarchy that represents the image at different
resolution levels is created. Next, top-down, object class knowledge
is used to select and combine regions from the hierarchy, in order
to define the exact object shape. We illustrate the usefulness of the
approach with four different object classes: sky, caption text, traffic
signs and faces.
Vilaplana, V. [et al.]. Object detection and segmentation on a hierarchical region-based image representation. A: IEEE International Conference on Image Processing. "2010 IEEE International Conference on Image Processing". Hong Kong: 2010, p. 3393-3396.