  Saliency detection has drawn a lot of attention of researchers in various
fields over the past several years. Saliency is the perceptual quality that
makes an object, person to draw the attention of humans at the very sight.
Salient object detection in an image has been used centrally in many
computational photography and computer vision applications like video
compression, object recognition and classification, object segmentation,
adaptive content delivery, motion detection, content aware resizing, camouflage
images and change blindness images to name a few. We propose a method to detect
saliency in the objects using multimodal dictionary learning which has been
recently used in classification and image fusion. The multimodal dictionary
that we are learning is task driven which gives improved performance over its
counterpart (the one which is not task specific).
