Saliency model for object detection: searching for novel items in the scene.

This Letter presents a new computational model of visual saliency. A new definition for saliency is proposed: saliency is novelty, which guides the deployment of visual attention. We define novelty as coming from regions that contain dissimilarities from the global scene. Our approach consists of two stages: First, obtain a global perspective. The global representation is obtained with a visual vocabulary. A novelty factor for each visual word is introduced according to the "repetition suppression principle." Second, obtain a local perspective. A local representation is achieved from the histogram of visual word occurrence. The metric of saliency is defined as the overall novelty factor of the visual words. Experimental results demonstrate good performance of the proposed model on complex scenes and fair consistency with human eye fixation data.