Visual Saliency Detection Based Object Recognition
نویسندگان
چکیده
Visual object recognition is an open and challenging problem in computer vision. Note that fixing the position of the objects is one of the difficult problems in the object recognition task. Biological visual system tends to find naturally the most informative regions in a scene. In this paper, we present an object recognition approach based on the visual saliency. Firstly, the most salient region is obtained as the appropriate position of the object with the visual saliency detection method. Secondly, the dense SIFT (Scale Invariant Feature Transform) features are extracted from the detected salient region to form the image representation by using the LLC (Local-constrained Linear Coding) mapping scheme. Finally, the object recognition is completed with a linear SVM classifier. We evaluate the proposed method on the Graz-02, Caltech-256 and Pascal VOC 2006 datasets and verify the influence of the visual saliency.
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