Image annotation using high order statistics in non-Euclidean spaces
We utilize the high-order dissimilarity among a triplet of images to depict image visual content. We utilize a maximum a posteriori algorithm to achieve relevance of each tag for input new images. We utilize the properties of images in non-Euclidean space to achieve precise annotations.
image annotation non-euclidean space maximum a posteriori dissimilarity diffusion distribution high-order statistics gaussian mixture model corel database experimentation