A salient hierarchical model for object recognition

Image saliency attempts to describe the most conspicuous part in an input image by mimicking human visual selective attention mechanism. Naturally, it could be adopted for improving object recognition. To demonstrate the effectiveness of saliency in object recognition, this paper proposes a salient hierarchical model. First, the traditional saliency model is modified for more robust saliency estimation. Second, the visual saliency detection method is combined with the Hierarchical Maximization model to provide more useful visual information for classification. Experimental results show that the improved saliency model extracts more accurate conspicuity, and the proposed salient hierarchical model outperforms Hierarchical Maximization model.