Automatic detection of salient objects and spatial relations in videos for a video database system
Image and Vision Computing
Robust Pose Recognition of the Obscured Human Body
International Journal of Computer Vision
A case-based reasoning approach for detection of salient regions in images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
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This paper describes a method for detecting salient regions in remote-sensed images, based on scale and contrast interaction. We consider the focus on salient structures as the first stage of an object detection/recognition algorithm, where the salient regions are those likely to contain objects of interest. Salient objects are modeled as spatially localized and contrasted structures with any kind of shape or size. Their detection exploits a probabilistic mixture model that takes two series of multiscale features as input, one that is more sensitive to contrast information, and one that is able to select scale. The model combines them to classify each pixel in salient/nonsalient class, giving a binary segmentation of the image. The few parameters are learned with an EM-type algorithm